reference group consumer behaviour

Methodology for the Analysis of Solid Waste (SWA-Tool)
User Version

Project:

SWA-Tool, Development of a Methodological Tool to Enhance the Precision & Comparability of Solid Waste Analysis Data

Program:

5th Framework Program, EU

Project Coordinator:

iC consulenten ZT GmbH, Austria

Contractors:

iC consulenten ZT GmbH

Austria

City Council of Vienna, MA 48

Austria

Technical University Berlin

Germany

University of Northumbria

UK

Gruppo Impresa Finance srl

Italy

Fundacion Gaiker

Spain

ICIM

Romania

Oil and Gas Institute

Poland

Newcastle City Council

UK

ASM Brescia spa

Italy

City of Bilbao

Spain

COMPREST

Romania

City of Cracow

Poland

Contact:

iC consulenten ZT GmbH, DI Gertraud Moser, Kaiserstrasse 45, A-1070 Vienna
Phone: +43 (1) 521 69-291, email: g.moser@ic-vienna.at; www.ic-vienna.at

Information available:

www.wastesolutions.org www.swa-tool.net M:\PROJEKTE\07 ABW\0103_SWA-TOOL\TOOL-END\SWA_TOOL_USER_VERSION_MAY_2004.DOC

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Table of Contents
1.

INTRODUCTION............................................................................................... 4

2.
2.1
2.2

Definitions........................................................................................................ 5
Waste Terminology and Scope ......................................................................... 5
Statistical Standards ......................................................................................... 6

3.
3.1
3.1.1
3.1.2
3.2
3.2.1
3.2.2
3.2.3
3.2.4
3.2.5
3.2.6
3.2.7
3.3
3.3.1
3.3.2
3.3.3
3.3.4
3.4
3.4.1
3.4.2
3.4.3
3.4.4

Waste Characterisation .................................................................................. 7
Pre-investigation ............................................................................................... 7
Background Information .................................................................................... 7
Stratification ...................................................................................................... 8
Analysis Design and Planning......................................................................... 11
Type of Sampling ............................................................................................ 11
Number and Type of Strata............................................................................. 11
Level of Sampling............................................................................................ 13
Type of Sampling Unit..................................................................................... 14
Calculation of the Number of Sampling Units and Sample Size ..................... 16
Generation of Random Sample Plan .............................................................. 19
Duration of an Individual Waste Analysis Campaign ...................................... 21
Execution of Waste Analysis........................................................................... 21
Collection of Samples ..................................................................................... 21
Sorting and Analysis of Samples .................................................................... 23
Important Points of Clarification for Sorting and Classification ....................... 25
Health and Safety............................................................................................ 25
Evaluation of Waste Analysis.......................................................................... 26
Evaluation of Raw Data................................................................................... 26
Quality Assurance ........................................................................................... 26
Extrapolation ................................................................................................... 27
Presentation of Results ................................................................................... 29

ANNEX I

Sorting Catalogue ......................................................................................... 32

ANNEX II
Part A
Part B
Part C
Part D

Statistical Background ................................................................................. 36
Theory Statistics.............................................................................................. 36
Example for Calculation of a Confidence Interval ........................................... 41
Determination of Number of Sampling Units and Sample Size....................... 42
Stratified Random Sampling Procedure.......................................................... 44

ANNEX III Health and Safety .......................................................................................... 45
ANNEX IV Cost of Waste Analyses ............................................................................... 48
ANNEX V Calculation Tables ........................................................................................ 51
ANNEX VI References..................................................................................................... 52

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Tables
Table 1
Table 2
Table 3
Table 4
Table 5
Table 6
Table 7
Table 8
Table 9
Table 10
Table 11
Table 12

Stratification Criteria.............................................................................................10
Details of Partner Cities Waste Analysis Stratification Criteria.............................12
Distribution of Inhabitants According to Stratification Criteria ..............................13
Sampling Units Used in Demonstration Phase ....................................................15
Calculation Necessary Number of Sampling Units (95 % Confidence Level) ......16
Examples Calculation of Sample Size from the SWA-Tool Project......................17
Special Cases during the Sorting Procedure .......................................................25
Example for the Presentation of Results..............................................................30
Distribution of tα;n−1 for Given Probability Levels ..................................................40
Content of Paper/Cardboard in Sampling Units ...................................................41
Calculation Necessary Number of Sampling Units (95 % Confidence Level) ......43
Summary of Cost Estimation of Waste Analysis ..................................................50

Table of Figures
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5

Schematic Example of a Multistage Stratified Random Sampling Process .........20
Example of Sampling (Sampling Unit is 1 m³)......................................................22
Sorting Procedure ................................................................................................24
Example for the Graphical Presentation of Results .............................................30
Example Comparison of Seasonal Primary Waste Composition .........................31

Table of Abbreviations
C.I.
Dev.
GNP
kg l m m³ mm n RCV
SWA-Tool
VarCoeff

Confidence interval
Deviation
Gross National Product
Kilogram
Litres
Metre
Cubic metre
Millimetre
Number of sampling units
Refuse Collection Vehicle
Solid Waste Analysis Tool
Variation Coefficient

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INTRODUCTION
This report will present a standardised methodology for the analysis of ‘solid waste’. It has been developed as part of the European Commission Fifth
Framework, ‘Solid Waste Analysis Tool’ (SWA-Tool) project.
The SWA-Tool aims to provide a waste analysis methodology for use at a local and regional level. It is therefore necessary to determine the information needs of the areas under investigation, including monitoring and reporting requirements necessary for effective waste management at these levels.
These local and regional needs, however, also operate within a wider framework of various regional, national, European Union or even international waste management requirements. The SWA-Tool methodology should take account of these wider requirements wherever possible in order to optimise synergy and relevance between the local and regional level and these wider levels.
The SWA-Tool does not aim to cover all municipal solid waste streams. It is therefore important to distinguish the scope of waste to be included as the parent population (whole quantity of waste in the survey area) within this methodology.
In the framework of this project municipal solid waste may be waste, which is collected by or on behalf of a municipality, via pick-up systems and/or drop-off systems depending on the municipality and the country. Such waste may derive from households, commerce, and industry and from municipality activities such as street cleaning or maintaining green spaces. As the collections system may differ for various communities municipal solid waste does not necessarily include the same categories of materials everywhere.
The methodology describes an approach for the representative sampling of the
‘residual solid waste’1 fraction of that portion of municipal solid waste described as “daily household and commercial waste”2. It also includes an approach for the manual sorting and analysis of such waste to determine the following:
1. Waste Characterisation (composition)
2. Waste Quantification (amount produced) based on waste composition
The methodology will establish minimum standards, which a waste analysis should always meet such as: sorting procedures; sorting categories; definition of statistical accuracy and common reporting guidelines. This will enable the comparability of results between different waste analyses.
In addition, different waste management regimes may operate at a local or regional level. A key aspect of the SWA-Tool methodology is that it should be capable of adaptation to differing local circumstances. The methodology will therefore provide additional criteria beyond the minimum standards to enable the user to select the most appropriate analysis design in relation to their specific local objectives and circumstances.

1

Residual solid waste is mixed solid waste from households and includes similar commercial mixed solid waste, which is co-collected.
2
As defined by the European Environmental Agency (EEA) report “Household and municipal waste:
Comparability of data in EEA member countries” (2000) www.eea.eu.int

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Chapter 2 is concerned with the definition of relevant waste terminology, the scope of waste to be considered and the overall statistical standards for a waste analysis. In addition an important part of the SWA-Tool project is the development of a standard system of waste classification (Annex 1); at present there is no standard system of waste terminology and waste category classifications for use in a solid waste analysis within the European Union.
Chapter 3 describes the methodology for waste characterisation and waste quantification. Besides the “user version” there is also a “long version” of the methodology available on the websites mentioned on the cover sheet. In some points the user version refers to the long version.
2.

DEFINITIONS

2.1

WASTE TERMINOLOGY AND SCOPE
The actual constitution of municipal waste varies between municipalities across the European Union. However, the fraction of municipal solid waste defined as
"daily household and commercial waste" which forms the scope of waste to be covered by the SWA-Tool methodology includes:
• Residual household waste which may be described as mixed solid waste from households, which is collected, transported, and disposed of, either by the household, the municipality or by any other third party in any kind of containers and/ or plastic bags; and
• Residual co-collected commercial waste which may be described as mixed solid waste from commerce, which is co-collected, transported, and co-disposed of, either by the household, the municipality or by any other third party in any kind of containers and/ or plastic bags. The composition of daily residual commercial waste is similar to the composition of residual waste from households. But the amount and composition arises in spatial clusters and depending on the business sector.
Not included in this kind of definition are:
• Separately collected household and commercial material streams such as glass, paper, plastics;
• Separately collected municipal waste streams which may include small scale hazardous waste, electrical/electronic waste, street cleanings, garden/park waste;
• Any other waste stream, which is not produced from routine activity such as bulky waste.

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STATISTICAL STANDARDS
As it is impossible to analyse the whole quantity of waste in a survey area (parent population), a sample (random sample) has to be taken. This sample has to be representative for the area of investigation and should describe the characteristics of the whole parent population.
The consistency of household/commercial waste is varied i.e. heterogeneous consisting of many different components or categories. Furthermore the size of waste particles ranges from mm (fine elements) up to 1 m (e.g. parts of furniture). In order to obtain statistically acceptable results for such heterogeneous conditions it is necessary to analyse a suitable sample size.
A key objective of this methodology is to enable waste analyses to achieve results at or above a minimum statistical accuracy in a cost effective way.
The minimum statistical standards demanded by the methodology are defined as follows:

Recommendation 1
Results shall be expressed on a 95 % confidence level
The value of relative accuracy of the total result (weight of the sampling units) shall be below 10 % (maximum allowance for random sampling error for the total results) The value of relative accuracy for the predominant categories (organic, paper and cardboard, plastic, glass, metal and fines) shall be below 20 % (maximum allowance for random sampling error)

A more detailed explanation of the statistical background to the above standards is contained in Annex 2: Statistical Background.

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WASTE CHARACTERISATION
An essential component of a waste analysis involves waste characterisation or the determination of waste composition. There are four recommended stages to waste characterisation as follows:
1. Pre-Investigation
2. Analysis Design and Planning
3. Execution of Waste Analysis
4. Evaluation of Waste Analysis

3.1

PRE-INVESTIGATION
The pre-investigation stage is concerned with the provision of necessary background information for the municipality, county or country intending to undertake a waste analysis. This should form the basis of the subsequent waste analysis planning stage where appropriate. It also provides some of the background necessary for an effective evaluation of the outcomes of a waste analysis. 3.1.1

Background Information

Recommendation 2
It is not recommended to collect all below mentioned data. Only data shall be collected which are important for the creation of a selection basis and which are needed to create the analysis design. This is very country specific and also might vary from case to case.

The following background information to a waste analysis is suggested:
1. General Description of the Area Under Investigation
A general overview of the area under investigation and the portion of the area to be involved in the waste analysis is recommended to provide a useful background context to the proposed study and assist in the planning stage. The following minimum information is suggested:
(i)
(ii)

Identification of the area or portion of the area to be assessed, its location and surface area;
Identification of the various relevant geo-political districts and the levels at which relevant waste management data may be available.

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2. General Population Information and Waste Management Information
General population information and waste management information is necessary to create a selection basis from which the representative sample can be generated. Therefore it becomes necessary to evaluate the factors which could influence the composition of waste in order to know which data have to be collected. The following data could be important to collect:
General Population Information
(i)
(ii)
(iii)
(iv)

Number of inhabitants
Number of households
Income (such as GNP per capita)
Types and proportions of residential structures

Waste Management Information
(i)

General description of the organisation of the waste management system
(actors, responsibilities etc.)
(ii) Type of waste streams produced and collected especially mixed residual household, and co-collected household and commercial waste
(iii) Description of waste container systems in use such as household bins, communal bins and bin storage capacities
(iv) Average numbers of households and/or persons using bins
(v) Total bin volume; spatial distribution of bins; collection intervals
(vi) Method of waste collection such as open truck or refuse collection vehicles compactor and types of waste collected
(vii) Description of collection rounds
(viii) Weighing data of collection vehicles
(ix) Disposal methods such as landfill, energy from waste, reuse/recycling and the types of waste and quantities involved.

3.1.2

Stratification
Stratification is the statistical subdivision of the in-homogenous parent population
(e.g. waste arising of an area) into (more) homogenous sub populations (non overlapping groups, e.g. waste from a certain residential structure), called strata.
The variation within strata is usually smaller than the overall population variance.
This causes two effects:
• A statistical stratification increases the accuracy of results at a given sample size or • a statistical stratification allows to reduce the sample size to reach an aspired level of accuracy
In waste analyses the main objective of stratification usually is to obtain specific results for single sub populations (e.g. waste from areas with gardening, waste from multi storey buildings, waste from different districts etc.). Here it is

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considered that specific parameters might have an influence on waste composition or waste amount.
An essential prerequisite is that the number of sampling units for each stratum is adequate to obtain reliable results of a certain accuracy for each stratum.
A “waste management stratification” aims at accurate results for sub populations.
Thus, the required number of sampling units has to be much larger than in case of a statistical stratification which usually aims at the improvement of accuracy of the total result of a waste analysis.

Recommendation 3
Generally, a stratification is not compulsory for a waste analysis program, but may have advantages for both, accuracy of results and additional waste management information.

Potential Stratification Criteria
A large number of factors may influence the composition or the amount of waste to be analysed and these may in turn vary in effect between municipalities; examples include:
•
•
•
•
•
•
•
•
•

Residential structure
Heating systems
Seasonal variations
Bin size
Availability of civic amenity sites
Holiday periods
Type of collection system (separate collection)
Levels of public education and awareness on waste issues
Etc.

An important aspect of the SWA-Tool methodology is to provide the users with sufficient information to enable them to determine which if any stratification criteria should be incorporated in their waste analysis design. This will also depend on the purpose of the waste analysis and the waste management conditions within the area of investigation.
Within the SWA-Tool project, a statistical analysis of data from past waste analyses within several cities and areas in Europe has been undertaken. The results of this investigation show that in some cases the applied strata did not demonstrate any statistical significance with regard to their impact on waste composition. However, based on this evaluation a number of stratification criteria may indeed have a significant influence on waste composition and could therefore form a useful part of a municipal waste analysis program:

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Table 1

Stratification Criteria

Stratification
Criteria
Seasonality

Residential
Structure

Bin Size

Collection
System

Source
Waste
(Household
Commercial
Waste)

Socioeconomic
Influences

Collection
Day

prepared by SWA-Tool Consortium
March 2004

Recommendation

Notes

Stratification according to seasons shall always be considered.
Generally, a seasonal waste analysis should be done based on a minimum of three and ideally four, seasonal sorting campaigns. Since waste analysis results tend to be similar for spring and autumn, one of these two seasons may be left out.
Generally, waste analysis stratification according to different residential structures and their locations can be recommended.

Household and commercial waste may be subject to significant seasonal variations in quantity and composition. The following types of residential structures and locations have been demonstrated to act as significant stratification criteria:
•
Rural areas
•
Suburban areas
•
Inner city areas
•
Multiple dwellings
•
Multi storey buildings

Generally, waste analysis stratification according to the following bin sizes can be recommended: •
Bins up to 240 litres volume
•
Bins above 240 litres volume
It has not been possible to provide definitive recommendations for potential stratification criteria based on different waste collection systems.

However it is reasonable to assume that there may be significant differences in waste composition between areas with and without separate collection of recyclables.
Therefore, assuming it is possible to delineate those areas with and without separate collection of recyclables this may be a potentially useful stratification criterion. of Generally, stratification according to the In most cases, waste from areas source of waste as either household waste with commercial activities is or or commercial waste is recommended significantly different to waste from where possible. residential areas.
It has not been possible to provide definitive recommendations for potential stratification criteria based on different socio-economic influences. However, these may be reflected within the criterion residential structure. A municipality may consider investigating these influences should sufficient planning information and resources be available.
Where a daily collection (excluding weekends) of all relevant waste is undertaken, it may be useful to compare the variation of waste amounts according to days of the week. In those cases where such waste data or operational information suggests a significant difference between waste composition/arisings between different days of the week, it is recommended these days be used as stratification criteria.

Methodology for the Analysis of Solid Waste (SWA-Tool)

In some cities/regions all the waste bins are collected every weekday.
In
these instances waste composition and amounts are often significantly different on Mondays, which tend to include weekend waste, compared to the remaining days of the week.
Potential strata could be Monday waste (including weekend waste) and another weekday (waste representative for the rest of the week). 10

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3.2

ANALYSIS DESIGN AND PLANNING

3.2.1

Type of Sampling
The parent population for a waste analysis campaign is the whole quantity of residual household waste and/or residual co-collected commercial waste, which may be sampled from and subsequently analysed. This may encompass the whole area of a municipality or a defined part of a municipality although the former will generally be the case in order to obtain waste analysis results, which are representative of the whole area under investigation. A sample refers to a subset of the parent population and it is necessary to work with waste samples because it is not possible to analyse the whole population of waste for the area under investigation.

Recommendation 4
It is recommended that stratified random sampling should be used, where possible, as the basis for sample selection for a local or regional waste analysis program. Whatever strata are chosen it is crucial that the relevant sources of waste to be sampled from, such as the waste bins, are capable of being attributed to, and sampled according to, the chosen strata.

For the theoretical background refer to “Methodology for the Analysis of Solid
Waste (SWA-Tool) – Long Version”.
3.2.2

Number and Type of Strata
Generally, a stratification is not compulsory for a waste analysis program, but may have advantages for both accuracy of results and additional waste management information (refer to Chapter 3.1.2).
Ultimately the decision concerning the number and type of strata to use in a waste analysis depends on several factors including the waste management information needs of the municipality, the availability of adequate waste planning data and sufficient resources.

Recommendation 5
It is recommended that not more than 5 relevant strata shall be used. The use of more than 5 strata would result in an excessive number of necessary samples
(larger sample size) in order to achieve the required accuracy of results for each stratum. Methodology for the Analysis of Solid Waste (SWA-Tool)

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Examples of the SWA-Tool Project
An integral part of the SWA-Tool project has involved a demonstration phase where the draft waste analysis methodology has been implemented in five of the project’s Partner Cities. Each Partner City has undertaken a waste analysis program, which was designed according to the draft methodology and the results of the evaluation of the stratification criteria whilst remaining appropriate to their local waste management circumstances. The number of waste analyses carried out and the stratification criteria used, varied between each of the cities.
Details of each City’s waste analysis program are shown in Table 2 overleaf.
Table 2

Details of Partner Cities Waste Analysis Stratification Criteria

Partner City

Chosen Stratification Criteria

Bilbao

Source of Waste as represented by type of district:
•
Residential
•
Commercial/residential
Day of Week:
•
Weekends (incl. Bank holidays)
•
Working Days

Brasov

Socio-Economic Status of Residents as represented by:
Residential Structure Type:
•
Single Dwellings
•
Multi-storey

Seasonal
Campaigns
Undertaken
Summer
Winter

Spring
Summer

Bin Size Single Dwellings:
•
120 litres
•
240 litres
Bin Size Multi-Storey:
•
240 litres
•
1100 litres
Brescia

Socio-economic Status of Residents as represented by
District Type:
•
Household Areas
•
Mixed Areas
•
Commercial Areas
Collection Weekday:
•
Mondays
•
Rest of Week

Summer
Winter
Spring

Krakow

Socio-Economic Status of Residents as represented by:
Residential Structure Type:

Spring
Summer

•
•

One family houses
Multi-storey

Collection Weekday:
•
After Weekend (including waste of the weekend)
•
Before of Weekend
Newcastle

Socio-Economic Status of Residents as represented by
Local Authority Grading of Property Values. (Council Tax
Bands):
•
•

Summer
Winter
Spring

Council Tax Band A and B (lowest value properties)
Council Tax Band “Others” (higher value properties combined) Methodology for the Analysis of Solid Waste (SWA-Tool)

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In practical terms it will be useful to set up a stratification matrix at the initial planning stage. This matrix will show if the necessary data and information for a stratification are available. As an example the table below shows the distribution of inhabitants depending on three residential structures and two groups of bin size. Table 3

Distribution of Inhabitants According to Stratification Criteria
A
Waste Bins 240 l

1 Suburban Areas

10%

5%

2 Inner-City Areas

30%

20%

-

35%

40%

60%

Stratification Criteria

3 Multi-Storey Buildings
Total

The example shows that two potential strata are of low importance (1B and 3A) and could be left out without influencing the result of the survey.
Furthermore the distribution according to strata is important to weigh the individual stratum and to bring together the results of the strata (see page 26,
Chapter 3.4.2).

3.2.3

Level of Sampling
The level of sampling is concerned with the position along the waste management process at which waste samples are taken for subsequent analysis.
There are three principal levels at which sampling may take place, namely:
1. Inside the household/business such as from an internal waste bin
2. Outside the household/business such as from an external waste bin/container such as used in kerbside collection
3. A refuse collection vehicle (RCV)

Recommendation 6
The recommended level of sampling of waste is the external waste bin/container outside the households or business properties.

A number of criteria have been applied in determining the most appropriate level at which to recommend sample selection. Primarily the sample level must enable the fulfilment of the statistical requirements as outlined earlier in Section 2.3. It should also allow the correlation and evaluation of household level stratification criteria such as residential structure and type of collection system with waste analysis results. Lastly the sample level should not compromise the process of

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manual sorting and analysis of waste such that it becomes hard to identify waste composition. Sampling of waste at the highest level, i.e. closest to the point of waste generation, occurs inside the house or business. This level of sampling does fulfil the necessary criteria, however there are two main disadvantages. The first relates to the practical difficulties, which would be encountered in accessing internal waste bins. In addition the actual composition of the waste sample could be unusually affected due to a change in waste generation behaviour by the household/business who would need to be informed of the planned occurrence and timing of the waste analysis.
Sampling of waste at the lowest level would occur from the refuse collection vehicle. Waste within an RCV consists of mixed household waste, preventing the correlation of waste analysis results with the influencing criteria of individual households/businesses. The process of mixing and usually compaction, results in the homogenisation of waste, decreased particle sizes and makes the visual identification of waste composition more difficult and time consuming. This can also increase the costs of the sorting and analysis stage. In addition it is necessary to obtain smaller sub-samples from the whole RCV load, for sorting and analysis. This procedure, such as by “coning and quartering”, increases the extent of statistical sampling errors and prevents the achievement of the required statistical standards (Section 2.3). Sampling from the level of collection vehicle does not therefore meet any of the necessary criteria as stated above.

3.2.4

Type of Sampling Unit
Sampling units are the smallest sub groups of the parent population which are separately selected, collected, sorted and analysed, and for which separate analysis results are produced.
There are three main sampling units that could be used to obtain the necessary waste samples for analysis, namely:
1. A specific waste bin volume such as 240 litres (l) or 1100 l; or
2. A specific weight of household/commercial waste such as 100 kilograms
(kg); or
3. A specific number of persons who generate relevant waste such as 30 persons. Recommendation 7
The recommended type of sampling unit should be based on the volume of the waste bin. (Please note this does not mean the volume of the waste contained within the bin.)

The use of waste bin/container volume as the sampling unit avoids disadvantages as described in “Methodology for the Analysis of Solid Waste
(SWA-Tool) – Long Version”.

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There is often a variation in the volume of waste bins/containers used by a municipality with the most commonly used volumes being 120 litres (l), 240 l,
1100 l, and 2400 l. The choice of the sampling unit will usually depend on the bin type which is most commonly used in the waste analysis study area, however where there is a choice available to a municipality the following should be noted:
•

The smaller the volume of the sampling unit the greater the statistical accuracy of results (relative accuracy at a given sample size of bin volume); and

•

The smaller the volume of the sampling unit the greater the time required for sorting and analysis for the equivalent sample size. This may be a consideration for those undertaking the actual analysis especially where this involves an external contractor.

Recommendation 8
The sampling units have to be of similar size.
The recommended sampling unit used for a waste analysis should be the lowest common denominator of bin size from the following: 120 l; 240 l; 360 l; 660 l;
1100 l; 2400; and 3600. Bins sampled for analysis, which are less than 120 l volume, should be aggregated to one of these sample sizes.
Example: Bins used are 120 l and 240 l. Sampling unit should be 240 l. Where
120 l bins are sampled then two of these bins should be aggregated to form one unit (240 l)

During the demonstration stage of the project the Partner Cities used a variety of sampling units. Table 4 shows the different sampling units used, the total sample size taken, and the estimated time for analysis.
Table 4

Sampling Units Used in Demonstration Phase

Partner
City
Brasov
Brescia
Krakow
Newcastle

Sampling Unit
1m3 (equivalent to the respective number of bins from 120 l, 240 l,
1100 l)
One 3200 litre container or one
2400 litre container
1m3 (equivalent to the respective number of bins from 120 l, 240 l,
1100 l)
One 240 litre bin (or the respective number of 120 litre bins) Methodology for the Analysis of Solid Waste (SWA-Tool)

Total Sample Size per Campaign
[m3]
45 m3
240 m3
45 m3
57 m3

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Calculation of the Number of Sampling Units and Sample Size
Calculation of Overall Number of Sampling Units
The total number of sampling units required depends on 2 main criteria:
1. The variation (heterogeneity) of the waste, expressed by the natural variation coefficient. This variation coefficient is usually unknown and has to be estimated on the basis of results from past waste analyses.
2. The desired accuracy of the results.
The required total number of sampling units for a waste analysis campaign can be easily estimated by using Table 5 below. It shows the necessary number of sampling units for different natural variation coefficients and different levels of relative accuracy of results (maximum random sampling error).
Usually the natural variation coefficient of the analysed waste is not known and has to be derived from empirical values from past waste analyses.
Applying this variation coefficient to the first column of Table 5 and reading across to the required level of accuracy (refer to Recommendation 1); 10% maximum random sampling error and 95 % confidence level, the necessary number of sampling units can be looked up. These values were calculated using equation 7 (Annex 2).
Table 5

Calculation Necessary Number of Sampling Units (95 % Confidence
Level)

natural variation coefficient
Gauge for variation in parent population)

necessary number of sampling units n
(95 % confidence level) with maximum allowance for random sampling error:
2.5%

5%

10%

15%

15%

138

35

9

20%

246

61

25%

384

96

30%

553

35%

20%

30%

4

2

1

15

7

4

2

24

11

6

3

138

35

15

9

4

753

188

47

21

12

5

40%

983

246

61

27

15

7

45%

1245

311

78

35

19

9

50%

1537

384

96

43

24

11

55%

1859

465

116

52

29

13

60%

2213

553

138

61

35

15

70%

3012

753

188

84

47

21

80%

3934

983

246

109

61

27

90%

4979

1245

311

138

78

35

100%

6147

1537

384

171

96

43

120%

8851

2213

553

246

138

61

140%

12047

3012

753

335

188

84

160%

15735

3934

983

437

246

109

200%

24586

6147

1537

683

384

171

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Recommendation 9
If the variation coefficient of the analysed waste is known (e.g. from former waste analyses in the same area) it should be used to calculate the required number of sampling units by using Table 5.

Recommendation 10
If the variation coefficient of the analysed waste is unknown the following sample sizes for the different types of waste are recommended (regardless of the size of the chosen sampling unit): household waste: mixture household/commercial waste: commercial waste:

45 m³
80 m³
100 m³

These values are based on experiences of former waste analyses and of the results of the SWA Tool project.
If the required accuracy is not reached with these values the sample size should be adjusted for the next seasonal campaign to achieve the required level of accuracy. Table 6

Examples Calculation of Sample Size from the SWA-Tool Project
Number of Sampling
Units
Sample Size [m³]
Necessary
Applied
Size of
VarCoeff Number of Number of xi Sampling Sampling
Campaign Sampling
Necessary
Applied
Difference
Unit [l]
(Sample)
no.
Units n
Units n
Sample Size Sample Size
[m³]

Brescia

3

2400

42%

68

75

163

180

17

Cracow

2

1100

37%

53

45

53

45

-8

Brasov

1

1100

23%

20

45

20

45

25

Newcastle

1

240

57%

125

230

30

55

25

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March 2004

Number of Sampling Units for Individual Strata
A certain amount (sample) of waste has to be analysed in order to obtain reliable results for a single stratum. The necessary number of sampling units depends on the variation of the waste (of the stratum) and the desired accuracy of the results.
The frame conditions are thus identical with those for the investigation of the parent population, i.e. if the relative accuracy of +/- 10% shall be achieved as the total result of a stratum, the same number of sampling units has to be investigated as in case of parent populations.
In practical terms, strata are usually analysed as a part of a total waste analysis and as such, with smaller sample sizes. In this case the results show a lower accuracy. If the sample size for strata goes beyond a certain level, results will probably be biased and are not representative.

Recommendation 11
The number of sampling units of one stratum per campaign shall exceed 6 and the sample size shall not be less than 6 m³ (bin volume) for household waste.
For commercial waste the number of sampling units of one stratum shall be 15 but the sample size shall not be less than 15 m³ (bin volume).
These are values of experiences.

Warning: Waste analysis results which are based on a sample size of only 6 m³ are afflicted with considerable uncertainties and shall not be over-interpreted.

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3.2.6

prepared by SWA-Tool Consortium
March 2004

Generation of Random Sample Plan
The generation of an appropriate random sample plan according to the analysis design is necessary to ensure the validity of waste analysis results and their subsequent evaluation. The sample plan also forms the basis of the collection addresses for the relevant waste samples.
A pre-requisite for the generation of a sample plan is the availability of a selection basis for the parent population of the waste analysis e.g. the addresses of all relevant waste containers. Ideally, this should be in electronic database or spreadsheet format to enable the easy manipulation and extraction of relevant address details.
According to the analysis design it is necessary to randomly sample addresses either from the whole parent population or from the relevant sub-populations according to the designated stratification criteria (stratified random sampling).

Recommendation 12
It is recommended that the generation of a random sample plan should also include the generation of a back-up set of random sample addresses. This additional random sample plan should be used to replace those primary addresses when the collection personnel determine it is not operationally possible to identify and collect the appropriate waste sample for analysis.

Example: Multistage stratified random selection
A suitable process for generating a representative waste sample is the multistage stratified random selection where several sampling operations are performed in succession. In order to achieve a multistage stratified random selection the entire survey area is initially arranged into strata. The attribution to particular strata is made on the basis of relevant background information and the preinvestigation survey for the area under study. At the level of the municipality information relating to waste management and socio-economic structure will be available to assist in the choice of relevant strata. The next stage involves the random selection of relevant sub units of statistic areas such as street blocks or enumeration districts. The final stage involves the random selection of waste bins from street blocks or enumeration districts.
In order to ensure representative sampling there must be an equal probability of selection at each stage of the process. This multistage approach ensures samples are selected randomly as part of a waste analysis study. Furthermore it simplifies the sampling procedure as detailed planning and data processing are only necessary for the lower stages of the selection procedure.
Note: Where it is necessary to select waste samples from residential blocks of flats it is acceptable to use waste bin registers or records for the selection of suitable sample waste bins without compromising the required level of accuracy.

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March 2004

The sampling plan for the multi stage stratified random selection is illustrated in
Figure 1.
Figure 1
Process

Schematic Example of a Multistage Stratified Random Sampling

Multi Stage Random Selection n statistical areas (in total)
U1 U2 U3 U4 U5 U6 ...

Analysis of clusters ... Un

Grouping the statistical areas according to strata (3 - 5),
e.g. industrial cities, other cities, countryside districts etc.
U1 U2 U5 U9 ... Un-3 U3 U4 U5 U17 ... Un-1

...

U6 U7 U8 U31 ... Un

...

U6 U7 U8 U31 Un

1st stage: random selection of statistical areas from each stratum
U1 U2 U13 U57 U256

2nd stage: random selection of sub-areas such as houseblocks U3 U4 U5 U17 Un-1

Random selection of sub-areas
U21 U22 U23 U24 ... U2m

U51 U52 U53 U54 ... U5m

...

U61 U62 U63 U64 ... U6m

Detection of the necessary parameter/data for each sub-area to select random samples with equal probabilities
3rd stage: random selection of bins

... sample unit
1.100 l

u231

Methodology for the Analysis of Solid Waste (SWA-Tool)

u541

...

u641

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3.2.7

prepared by SWA-Tool Consortium
March 2004

Duration of an Individual Waste Analysis Campaign

Recommendation 13
Where the normal municipal waste collection for the relevant parent population is repeated on a daily or weekly basis it is recommended that the duration for waste sampling and sample collection covers a minimum of one weeks waste. This will allow the sampling of waste to be spread over each working day
(Monday to Friday) covering the full collection cycle and any potential variation due to non-collection of waste at a weekend.

Recommendation 14
Where the normal municipal waste collection for the relevant parent population is repeated on a bi-weekly (fortnightly) basis it is recommended that the duration for waste sampling and sample collection cover a minimum of two weeks waste i.e. the full collection cycle.

3.3

EXECUTION OF WASTE ANALYSIS

3.3.1

Collection of Samples

Recommendation 15
The collection team should collect the sampling units from the predetermined properties by emptying or exchanging the selected container on the day of the regular collection interval. Ideally this should be done without informing the property holder responsible for the production of the waste to avoid unduly influencing its composition.
NOTE: to avoid cluster effects, do not take more than one sampling unit per sampling address.

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March 2004

Recommendation 16
Each sample collected should be tagged with a unique identification reference code, capable of use in wet conditions. The following minimum data should be collated and recorded for each individual sample by the waste sample collection team at the time of collection
(i)
(ii)
(iii)
(iv)
(v)
(vi)

Unique identification reference code
Sample address
Date of collection
Number and type of waste containers collected
Visual estimation of % filling level of waste containers collected
Visual estimation of % filling level of other containers at one address to get the information for calculating the waste quantity

Further information, which may be useful for the evaluation of results if easily available concerns the number of persons responsible for waste production at the sample address and the collection interval. Where this information is not available general statistical information for a municipality concerning the average number of persons per property may be available. This information could then be useful to provide an indication of per capita waste statistics in addition to per household waste statistics.
It is important that each individual waste sample collected is not mixed with any other waste samples during collection, transportation and subsequent analysis.
Once a full load of samples has been collected they should then be transported to the appropriate facilities for sorting and analysis.
An outline example of the collection process is shown in Figure 2. The sampling level is the external waste bin/container outside the households. In this case the sampling unit is 1 m³, here represented by 4 x 240 l bins.
Figure 2

Example of Sampling (Sampling Unit is 1 m³)

Sampling from each stratum

Data acquired during sampling:
- Address
- Numbers of bins and volume of bins
- Level of filling
- Collection interval

Sampling
Units

manual sorting
(for each sample unit)

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3.3.2

prepared by SWA-Tool Consortium
March 2004

Sorting and Analysis of Samples
Each sampling unit is weighed and the weight is documented. Each sampling unit has to be sorted separately. The sampling unit is sorted into the categories according to a developed Sorting Catalogue (see Annex 1).
The Sorting Catalogue contains 13 compulsory primary categories and 35 recommended secondary waste categories. To further assist sorting and analysis the catalogue also provides indicative examples for each secondary category for a wide range of items commonly encountered in the municipal waste stream as a guide to their appropriate classification. In addition, it is also possible to designate further tertiary or third level categories that may provide additional waste composition details according to their local waste information requirements. Recommendation 17
1

A waste analysis record sheet (paper copy) is set up for each sampling unit. 2

The unique identification code attached to each sample is recorded against the waste analysis record to be completed.

3

The percentage-filling ratio of the waste sample container (bin) is recorded.

4

The sampling unit is weighed to an accuracy of +/- 0.1 kilograms (kg) and the weight recorded.

5

In order to reduce the sorting effort, the sampling units can be separated into two initial fractions; above 40mm and below 40mm, by screening with a
40mm mesh screen (tromel). Alternatively the waste can be sorted directly on a 40 mm screen table. This step is an aid for the sorting team but not compulsory. 6

The above 40mm fraction is sorted into one of 12 compulsory primary waste categories excluding the ‘Fines’ category as specified by the SWATool Sorting Catalogue (Annex 1). The weight of each category is recorded for the sampling unit to an accuracy of +/- 0.1 kg.

7

The ‘below 40mm’ fraction is further screened with a 10mm mesh screen into two fractions; ‘below 10mm’fraction and ‘a 10-40mm’ fraction.

8

The ‘below10’mm fraction is weighed to an accuracy of +/- 0.1 kg and this weight recorded as the primary category ‘Fines’ according to the SWA-Tool
Sorting Catalogue (Annex 1)

9

The ‘10-40mm’ fraction is weighed, too. By coning and quartering a representative sub sample is generated and sorted according to the recommended primary waste categories specified in the Sorting Catalogue
(Annex 1). The observed composition of the sub-sample is then applied to the total weight of the 10-40 mm fraction. The resulting weights are recorded and allocated to the corresponding primary waste categories.

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Figure 3

prepared by SWA-Tool Consortium
March 2004

Sorting Procedure
Waste
Composition
1
2
3

Waste for Analysis

Screening
40 mm

> 40 mm

Manual Sorting

4
5

< 40 mm

n-1

Subsample
Screening
10 mm

n

10-40 mm Fines < 10 mm

Recommendation 18
It is recommended that the determination of the optimum number of sorting team personnel according to local circumstances, should be based on a waste sorting rate of 6 man-hours per 100 kilograms of waste (refer to Annex 4).

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3.3.3

prepared by SWA-Tool Consortium
March 2004

Important Points of Clarification for Sorting and Classification3
It is important to note that the application of any of these points of clarification must not supersede relevant Health and Safety Regulations and Guidelines.
Table 7
Item

Special Cases during the Sorting Procedure
Description

Packaging Items Packaging with contents with Contents where the content of a packaging item is suspected to weigh more than the packaging itself

Recommendation

Examples

The liquid content and the packaging filled bottles shall be classified separately to the specific categories of the Sorting
Catalogue.

Fraction < 10 mm in bags such as vacuum bags, house sweepings, litter for pets etc.

Therefore, these bags shall be classified with their content directly to the fraction < 10mm. These bags shall not be emptied, also for hygienic reasons. vacuum bags, house sweepings, litter for pets

Composites or combined packaging where the compounds can be separated easily The recommended Composites or combined packaging classification of these items where the compounds can be depends on whether they separated easily and which are of significant size or not
•
have a bigger size than a
(greater or smaller than a packet of cigarettes: the packet of cigarettes). compounds shall be classified to the specific categories.
•
have a smaller size than a packet of cigarettes: the compounds shall be classified to the prevailing category.

packets of cigarettes, bottles with cap, yogurt pots with alu lids Items consisting mainly of pure categories and only small parts
(< 20 % of weight) of other categories Liquids in waste bins 3.3.4

The contents of such bags are often easy to classify as fines and the weight of the bag forms a relatively minor part of the waste stream.

The separation of the different materials would be possible but with substantial effort of the sorting staff.

Due to the easy classification and the small error occurring within the sorting analysis these items are classified according to the category of its main component. handle bar (with handles of plastic), hole puncher, ring binder

These liquids are produced in waste bins during the degradation of the biological fraction. Usually these liquids rest on the bottom of the waste bin and shall be collected when the waste bin is emptied.

Due to the easy classification and the small error occurring within the sorting analysis these liquids shall be classified separately. They can be classified to the primary category
“Organic”.

Health and Safety

Note: The Health and Safety Recommendations contained in this methodology
DO NOT replace statutory Health and Safety rules in the respective countries for municipalities, but are intended as added guidance only (refer to Annex 3).
3

Refer to: LANDESUMWELTAMT BRANDENBURG (1998): Richtlinie für die Durchführung von Untersuchungen zur Bestimmung der Menge und Zusammensetzung fester Siedlungsabfälle im Land Brandenburg, Teil 1,
Fachbeiträge des Landesumweltamtes Nr. 34, Potsdam

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3.4

EVALUATION OF WASTE ANALYSIS

3.4.1

Evaluation of Raw Data
The basis for the evaluation are the basic weight results of the sorting procedure
(waste composition in kilograms) for each sampling unit.

Recommendation 19
The basic weight results shall be transferred from the record sheet (paper copy) to the Excel sheet (Annex 5). This Excel template will automatically calculate the waste composition and the required statistical data.

3.4.2

Quality Assurance
The following statistical values have to be calculated for each waste category, each campaign and for the total result:
(i)
(ii)
(iii)
(iv)
(v)
(vi)
(vii)
(viii)

Mean
Median
Standard deviation
Variation coefficient
Confidence coefficient (refers to tables of t-distribution, Annex 2)
Relative confidence interval (%)
Confidence interval (kg)
Composition (%)

Note: The statistical parameters are calculated on the basis of kg and should not be converted into percentages.
It is necessary to review the statistical results of each individual waste analysis campaign and for the overall waste analysis campaign to determine whether the desired statistical requirements of the SWA-Tool methodology (refer to Section
2.3).
In case a stratification has been applied, the results of the single strata have to be aggregated to obtain the total sample result. The total sample result has to be calculated as the weighted mean of the single stratum results.

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Recommendation 20
The result of each stratum has to be weighted (example see stratification matrix, page 13) and put in the right relation. The total result is the weighted mean of the single stratum results (see Annex 2, equation 8)
For the calculation of errors of the total sample result of each campaign formula
10 (Annex 2) has to be used.

3.4.3

Extrapolation
The extrapolation comprises the conclusion from the obtained sample results to the parent population. Two cases may be distinguished:
Case 1:
The investigated waste type of an area (e.g. daily household and commercial waste) is permanently weighed. Thus, the total waste amount is known. The total sample result (waste composition) can be apportioned to the total waste quantity
(parent population).
Case 2:
The total amount of the investigated waste type is unknown. This is the case if only household waste is subject of the waste analysis, but is not weighed separately (only the mixture of household and commercial waste is weighed).
Hence, an extrapolation of the sample results to the parent population (here: household waste of an area) is necessary. The following recommendations should be considered.
The waste quantity can be extrapolated by using the following data as a reference value:
• number of sampling units, or
• number of inhabitants, or
• number of households.

Recommendation 21
The total arisings of e.g. household residual waste can be calculated by multiplication of the total sample mean by the total number of sampling units
(parent population).

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Recommendation 22
(i)
In case of a stratification, the total arisings of e.g. household waste for a stratum should be calculated by multiplication of the stratum sample mean by the total number of sampling units within the stratum.
(ii) To obtain the total waste amount, the results of the strata have to be added
(please refer to the example below). The confidence interval for a stratified sample can be calculated by using equation 10 and 11 (Annex 2).
(iii) In case of a stratification, the total arisings of e.g. household waste the total waste amount can alternatively be calculated by multiplication of the weighted mean of the individual sample means by the total number of sampling units for the area under investigation.

Example Newcastle, UK
1 Sampling unit = 240 litres
Number of strata: 2
Number of sampling units within Stratum A = 30,000
Number of sampling units within Stratum B = 60,000
Stratum A: mean household waste arisings per week = 16 kg +/- 10%
Total waste arisings per week = (16 kg x 30,000) +/- 10%
= 480 tonnes +/- 48 tonnes
Stratum B: mean household waste arisings per week = 18 kg kg +/- 8%
Total waste arisings per week = (18 kg x 60,000) +/- 8%
= 1,080 tonnes +/- 86.4 tonnes
Addition of the results of the single strata = 1,560 tonnes
The total confidence interval has to be calculated using equation 10 and 11
(Annex 2).

Recommendation 23
Where a seasonal analysis involving less than four seasonal campaigns has been undertaken it may also be necessary to adjust the extrapolation of results to account for the missing seasonal investigation(s).

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3.4.4

prepared by SWA-Tool Consortium
March 2004

Presentation of Results
The format for the presentation of results is an important aspect of the waste analysis methodology and will affect the comparability of waste analysis results between different waste analyses. The fundamental aim of the SWA-Tool methodology is to improve the accuracy and comparability of municipal waste management statistics and the format of presentation can assist in optimising this. Recommendation 24
It is recommended to report and present the following data:
1. Raw Data (example see Annex 5)
Raw data should be presented and reported as an MS Excel table according to the format shown in Annex 5.
2. Statistical Calculations
Statistical calculations should be presented and reported as an MS Excel table according to the format shown in Table 8. The formulas for the calculation of the statistical parameters are included in this Excel template (Annex 5).
The relative confidence interval has to be calculated and represented as result.
Very often the absolute confidence interval is shown which depends on the corresponding mean. Therefore, it is not possible to compare results of different waste analyses.
3. Evaluation of single results of strata
The evaluation of single results of each stratum should be presented and reported as a table.
4. Extrapolation of the overall results and of the waste quantification
The extrapolation of results should be reported.
5. Graphical presentation of results
The mean waste amounts of the primary waste composition categories where calculated, should also be presented graphically as MS Excel Graphs in a similar format to that in Figure 4 and Figure 5 overleaf.

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Table 8

prepared by SWA-Tool Consortium
March 2004

Example for the Presentation of Results

Error Estimation
Composition

Confidence Interval (95%-level)

Sample
Composition

Total Amount

% weight

kg/cap.,week

kg/week

Variation
Coefficient

Variation
Coefficient

(sample)

Categories

Amount per
Capita

(estimator)

%

Dev. from the
Mean in

Lower Limit

Upper Limit

%

% weight

kg/week

kg/week

Total

Figure 4

34,1
1,0
22,1
9,6
7,0
3,1
5,0
0,5
5,0
7,6
4,1
1,0

5,9
0,2
3,8
1,7
1,2
0,5
0,9
0,1
0,9
1,3
0,7
0,2

3.168,2
92,5
2.050,4
896,9
654,7
289,8
461,4
43,9
464,2
701,9
384,3
91,6

88,0
729,2
88,0
73,9
136,1
262,6
107,6
508,1
419,7
472,3
245,7
419,1

3,8
31,4
3,8
3,2
5,9
11,3
4,6
21,9
18,1
20,4
10,6
18,1

7,4
61,6
7,4
6,3
11,5
22,2
9,1
42,9
35,5
39,9
20,8
35,4

2.932,5
35,5
1.898,0
840,9
579,4
225,5
419,5
25,1
299,5
421,8
304,5
59,1

3.403,8
149,5
2.202,8
952,9
730,0
354,1
503,4
62,8
628,8
982,1
464,1
124,0

100,0

Organic
Wood
Paper and Cardboard
Plastics
Glass
Textiles
Metals
Hazardous Waste
Complex Products
Inert
Other Categories
Fines < 10 mm

17,4

9.300,2

63,7

2,8

5,4

8.799,8

9.800,7

Example for the Graphical Presentation of Results

inert
8%

other
4%

fines
1%

complex
4%

hazardous
1%

organic
35%

metals
5%
textiles
3%
glass
7%
plastics
9%

wood
1%

paper & card.
21%

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Figure 5

prepared by SWA-Tool Consortium
March 2004

Example Comparison of Seasonal Primary Waste Composition

40,00

Septem ber Com bined

35,00

January Com bined
June Com bined

30,00

Waste composition %

25,00

20,00

15,00

10,00

5,00

0,00 or gani c

wood

paper &car d.

pl asti cs

gl ass

texti l es

metal s

hazar dous hhw compl ex

i ner t

other

f i nes

Waste category

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ANNEX I

prepared by SWA-Tool Consortium
March 2004

SORTING CATALOGUE
Primary
Categories

Code

Code
OR1 01

OR1 02

Other
Waste

OR1 03

Biodegradable

Notes

Typical Examples

All biodegradable waste originating in domestic kitchen or commercial/industrial canteen
All
biodegradable waste originating in a domestic garden or municipal park, garden, or landscaping feature
All biodegradable waste not applicable to either of the above categories
All wood/cork items without paint, varnish, preservative, sealant etc
All wood/cork items with paint, varnish, preservative, sealant etc

Bread; Coffee grinds; Cooked or Uncooked food items; Food leftovers;
Fruit and vegetables; Meat and fish; Pet foods; Tea bags
Flowers; Fruit and vegetable garden waste; Grass Cuttings; Hedge trimmings; Leaves; Pruning; Tree branches; Weeds

Animal remains; Bones
Faeces

W2 02

High gloss paper/card and wallpapers PC3 01

Non-biodegradable paper

Glossy brochures e.g. travel brochures; shop catalogues
Glossy magazines e.g. Cosmopolitan, Elle
High gloss papers e.g. photographic papers
Waste wallpapers

PC3 02

All non-glossy paper card packaging Cereal packets; Cleaning product cartons; Corrugated packaging cardboard (bulk and individual); Fast Food Paper bags/wrapping; Noodle and egg boxes; Other food/pet food/ non-food container packaging;
Paper bags; Tissue boxes; Toy boxes; Washing powder boxes; Waxed card liquid cartons; Wrapping paper

Newspapers

PC3

W2 01

Paper/card – packaging

Paper and Cardboard

Untreated Wood
Treated Wood

Wood

W2

Biodegradable
Kitchen/Canteen Waste
Biodegradable
Garden/Park Waste

Organic

OR1

Secondary
Categories

PC3 03

Loose and stapled newsprint

Local and national newspapers (paid and free)
Newsprint-type advertising publications; Other newsprint

PC3 04

All paper card otherwise not mentioned Birthday type cards; Books; Computer printouts; Diaries; Envelopes;
Files and folders; Invoices; Kitchen roll; Letters; Loose leaf paper; Non glossy brochures and catalogues; Non-glossy junk mail; Office paper;
Photocopies; Posters; Telephone directories; Tickets; Tissue paper;
Toilet papers; Writing paper; Yellow pages

Other Paper/card– packaging Methodology for the Analysis of Solid Waste

non

Bottle corks, Cork packaging, Untreated Pallets
Solid timber and timber fragments untreated
Particle board (e.g. chipboard, plywood, mdf)
Solid timber and timber fragments, treated
Wood fencing- treated; Wood from DIY - treated
Wood furniture – treated; Wood kitchen units- treated
Wood work tops- treated

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Primary
Categories

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March 2004

Code

Code

Plastic Film –packaging

Notes

Typical Examples

PL4 01

All packaging refuse sacks

and

Biscuit wrappers; Cereal packets (inside box); Cling film; Compost/peat bags; Crisp packets; Frozen food bags; Packaging plastic film; Plastic food bags/pet food/non food bags; Sandwich bags

non

PL4 02

All non packaging bags and refuse sacks

Cellotape; Garden sheets; Non-packaging film; Plastic bags; Refuse sacks; Shopping bags; Tarpaulins

Dense Plastic Bottles/Jars
(P)

PL4 03

All clear and coloured plastic bottles and jars

All plastic bottles/jars e.g.; Alcoholic drinks; Bleaches; Detergents;
Household/pet/garden products; Laundry liquid; Milk; Oil; Soft drinks;
Vinegar; Water

Dense Plastic packaging other

PL4 04

All other clear and coloured plastic packaging except bottles and jars

Appliance packaging; Cleaning tubes; Cosmetic tubes; Egg boxes; Food cartons; Food packing trays; Food tubes; Ice cream cartons; Margarine tubs; Plastic lids; Ready meal trays; Roll on deodorant bottles; Trays;
Yoghurt cartons; Bottle tops

–non

PL4 05

All non-packaging plastic items

dense

Air freshener holders; Bank/credit cards; Buttons; CDs'; music cassettes;
Cosmetic/glue/paint applicators; Disposable razor blades; Floor Linoleum
(Lino); Floor Tiles (vinyl/plastic); Garden hoses; Gardening equipment;
Hard plastic; Household/car/garden accessories; Lighters; LPs; Pens;
Plant pots; Plastic curtain rails; Plastic frames; Plastic sunglasses;
Plastic toys; Rulers; Rulers; Seed trays; Shoes (Plastic only); Toilet lids;
Toothpastes; Tubes/pumps; Video cassettes; Washing up bowls/racks

Glass Container Packaging
Clear

G5 01

All clear glass bottles and jars

Glass Container Packaging
Brown

G5 02

All brown glass bottles and jars Alcoholic and non-alcoholic drinks bottles/jars (e. g. beer, cider, milk, water, wine)
Food jars (e.g. baby foods, coffee, jams, pickles, sauces)
Medicine bottles
Alcoholic and non-alcoholic drinks bottles/jars (e.g. beer, cider, milk, water, wine)
Food jars (e.g. baby foods, coffee, jams, pickles, sauces)
Medicine bottles

Glass Container Packaging
Other

G5 03

All coloured glass bottles and jars except brown and clear glass Alcoholic and non-alcoholic drinks bottles/jars (e.g. beer, cider, milk, water, wine)
Food jars (e.g. baby foods, coffee, jams, pickles, sauces)
Medicine bottles

Miscellaneous
Packaging Glass

Plastics

PL4

Secondary
Categories

G5 04

All non-packaging glass

Cookware (e.g. pyrex, drinking glasses)
Flat glass (e.g. table top, window, mirrors, reinforced, windscreens)
Light bulbs (e.g. normal, fluorescent, energy saving
Mixed broken glass
Television/ computer screens separated only

Plastic
Film
packaging

Dense
Plastic
packaging

Glass

G5

Methodology for the Analysis of Solid Waste

–

–

Non

bags

33

European Commission
Project: Solid Waste Analysis-Tool
Primary
Categories

prepared by SWA-Tool Consortium
March 2004

Code

Code

Complex
Products

C9

Trousers; Skirts; Socks; Stockings; Tights; Underwear; Shirts; Blouses;
Jumpers; Cardigans; Coats; Hats; Gloves

M7 01

Ferrous food, beverage and non-food cans and containers

M7 02

All non-ferrous Cans and
Containers and Aluminium
Foils etc.

Biscuit containers; Packaging for carbonated drinks, Fish, Pet food etc.;
Shoe polish cans; Soft drinks; Soups; Sweets; Tinned food; Aerosols
(deodorant, perfume, hairspray)
Aluminium foil sheets; Biscuits containers; Cake and pie containers;
Carbonated drinks; Containers; Fish; Pet food; Shoe polish cans; Soft drinks; Soups; Sweets; Take away; Tinned food; Other food/non-food/ pet food containers; Aerosols (deodorant, perfume, hairspray)

M7 03

All ferrous items except food, beverage and non-food cans and containers

Bike parts; Building materials/DIY materials; Car parts; Cutlery; Keys;
Licks; Metal shelves; Nails; Paper clips; Plumbing; Pots and pans;
Radiators; Ring pulls; Safety pins; Screws; Tools

M7 04

Batteries/Accumulators

H8 01

H8 02

All non-ferrous items except
Aluminium
Cans and Containers and Aluminium
Foils
All types of household and car batteries including rechargeable and nonrechargeable
All
other potentially hazardous household type waste Keys; Cutlery; Locks; Ring pulls; Tools; Car parts; Radiators; Metal shelves; Pots and pans; Screws; Nails; Building materials/DIY materials;
Plumbing; Bike parts

Miscellaneous waste H8

Natural and man-made clothing items excluding shoes
Natural
and man-made textiles and furnishings except clothes and shoes

Miscellaneous Non-ferrous

Hazardous
Household
Waste

T6 02

Ferrous Packaging

Typical Examples

Miscellaneous Ferrous

M7

T6 01

Notes

Non-ferrous Packaging

Metals

Clothes
Non-clothing textiles

Textiles

T6

Secondary
Categories

Any complex/composite packaging that cannot be easily separated into its component materials and is therefore difficult to classify conventionally Any complex/composite item which is not packaging that cannot be easily separated into its component materials and is therefore difficult to classify conventionally

Aluminium Foil-coated card, liquid containers e.g. milk; fruit juice

hazardous

Composite/Complex
Packaging

Composite/Complex packaging Methodology for the Analysis of Solid Waste

C9 01

Non-

C9 02

Balls of wool; Blankets; Braids; Carpets; Cloths; Cords; Curtains;
Household soft furnishings and upholstery; Mats; Pillow cases; Pillows;
Rags; Ropes; Rugs; Sheets; Threads; Towels

Lead acid
Nickel cadmium
Other car and household batteries and accumulators (including rechargeable batteries
Asbestos; Cooking oils; Fire extinguishers; Garden/household chemicals;
Glues and solvents; Medicines; Methylated spirits; Mineral, synthetic and non-edible organic oils and fats and their filters; Motoring products; Paint products; Photo chemicals; Refrigerants; White spirits

Appliance parts
Car parts
Engine parts
Sandals (multi-material only)
Shoes (multi-material only)

34

European Commission
Project: Solid Waste Analysis-Tool
Primary
Categories

prepared by SWA-Tool Consortium
March 2004

Code

Secondary
Categories

Code

Complex
Products

C9

Mixed WEEE

C9 03

Inert

IN10

Soil and Stones

IN10 01

Miscellaneous inert

IN10 02

Nappies

Notes
Large Household Appliances
Small Household Appliances
IT and Telecommunications
Equipment:
Lighting Equipment:
Toys:
Monitoring and control instruments: U11 01

Typical Examples
Air conditioners; Answering machines; Car racing sets; Carpet sweepers;
Clocks; Clothes dryers; Coffee makers; Compact fluorescent lamps;
Computers; Cookers; Copiers; Dishwashers; Drills; Electric knives;
Electric stoves/hotplates; Electric toothbrushes; Electric trains; Electrical and Electronic Tools; Fax; Freezers; Fryers; Hair dryers; Hand held video game consoles; Heating appliances; Heating regulators/thermostats; High intensity discharge lamps; Irons; Laptops;
Large cooling appliance; Low pressure sodium lamps; Microwaves; PCs;
Printers; Refrigerators; Saws; Scales; Sewing machines; Shavers;
Smoke detector; Straight fluorescent lamps; Telephones/Mobile phones;
Telex; Toasters; Vacuum cleaners; Video games; Washing machines
Boulders; Bricks; Gravel; Pebbles; Sand; Soil; Stones

U11

Ceramics
Clay plant pots
Crockery
Stone/ceramic floor and wall tiles
Vases
Children’s disposable nappies

U11 02

Household Medical Waste

Dressings
Swabs
Syringes

Miscellaneous Categories

Other
Categories

Any ‘Inerts’ except soil and stones U11 03

Any other material that is difficult to classify under any other categories

10mm sieved fraction

F12 01

Health
Wastes

Fines

F12

Methodology for the Analysis of Solid Waste

Care/Biological

Ashes
Sand
Small fragments