Further development of the European reference model on waste generation and management : final report.
Date: 2015-12-04
Institutions: Directorate-General for Environment
Subjects: EU environmental policy, environmental economics, environmental impact, environmental law, environmental protection, report, waste management, waste recycling

Further development of the 
European reference Model on Waste 
Generation and Management"    

Final report 

May – 2015 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Title of the document 

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Luxembourg: Publications Office of the European Union, 2015 

ISBN 978-92-79-53753-0 
doi:10.2779/871316 

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FURTHER DEVELOPMENT OF 
THE EUROPEAN REFERENCE 
MODEL ON WASTE 
GENERATION AND 
MANAGEMENT 

FINAL REPORT 

Dr Dominic Hogg 

Thomas Vergunst 

Timothy Elliott 

Laurence Elliott 

Mark Corbin 

Ann Ballinger 

28th May 2015 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Report for Michel Sponar, DG Environment of the European Commission 

Prepared by Dr Dominic Hogg,Thomas Vergunst, Timothy Elliott, 
Laurence Elliott, Mark Corbin, and Ann Ballinger 

Approved by  

Dominic Hogg 

(Project Director) 

Eunomia Research & Consulting Ltd 
37 Queen Square 
Bristol 
BS1 4QS 

United Kingdom 

Tel: +44 (0)117 9172250 
Fax: +44 (0)8717 142942 

Web: www.eunomia.co.uk 

Disclaimer 

Eunomia Research & Consulting has taken due care in the preparation of this report to 
ensure that all facts and analysis presented are as accurate as possible within the 
scope of the project. However no guarantee is provided in respect of the information 
presented, and Eunomia Research & Consulting is not responsible for decisions or 
actions taken on the basis of the content of this report. 

 
 
 
 
 
 
 
 
 
 
 
 
FINAL REPORT  

i 

 
 
Contents 

1.0 

2.0 

Introduction ...................................................................................................... 1 

Results of Additional Model Simulations ............................................................. 3 

2.1  Changes to the Model ....................................................................................................... 4 

2.2  65% Preparation for Reuse and Recycling Target ........................................................... 7 

2.2.1 

Change in Final Management Destinations ............................................................. 7 

2.2.2 

Financial Costs ............................................................................................................ 8 

2.2.3 

Environmental Costs................................................................................................. 10 

2.2.4  Net Social Costs and Employment ........................................................................... 10 

2.3  65% Preparation for Reuse and Recycling Target with Derogations ........................... 12 

2.3.1 

Change in Final Management Destinations ........................................................... 12 

2.3.2 

Financial Costs .......................................................................................................... 13 

2.3.3 

Environmental Costs................................................................................................. 14 

2.3.4  Net Social Costs and Employment ........................................................................... 15 

2.4  New 70% MSW Recycling Target ................................................................................... 17 

2.4.1 

Change in Final Management Destinations ............................................................. 1 

2.4.2 

Financial Costs ............................................................................................................ 0 

2.4.3 

Environmental Costs................................................................................................... 1 

2.4.4  Net Social Costs and Employment ............................................................................. 2 

3.0 

Model Sensitivities ............................................................................................ 5 

3.1  Key Parameters ................................................................................................................. 5 

3.2  Approach to Analysing Sensitivities ................................................................................. 6 

3.3  Results of Sensitivity Tests................................................................................................ 7 

4.0 

Modelling C&D Waste Flows ............................................................................ 18 

4.1  Overview of C&D Model ................................................................................................. 18 

4.1.1  Data Inputs and Assumptions.................................................................................. 18 

4.1.2  Modelled Scenarios .................................................................................................. 20 

4.1.3  Waste Flow Projections............................................................................................ 20 

4.1.4  Assessment of Impacts ............................................................................................. 20 

4.2 

Full Implementation Scenario ........................................................................................ 21 

4.2.1 

Change in Final Management Destinations ........................................................... 22 

4.2.2 

Employment Impacts ............................................................................................... 23 

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4.2.3 

Costs and Benefits .................................................................................................... 24 

4.2.4  Net Costs and Benefits ............................................................................................. 25 

4.3  More Ambitious Scenario ............................................................................................... 27 

4.3.1 

Change in Final Management Destinations ........................................................... 27 

4.3.2 

Employment Impacts ............................................................................................... 28 

4.3.3 

Costs and Benefits .................................................................................................... 29 

4.3.4  Net Costs and Benefits ............................................................................................. 30 

Member State Summary Reports ...................................................................... 32 

Modelling Imports and Exports of Municipal Solid Waste in Europe  .................... 33 

5.0 

6.0 

6.1  Reviewing the Available Data ......................................................................................... 33 

6.1.1  Member State Reporting Requirements ................................................................. 33 

6.1.2 

Preparation for Reuse and Recycling ...................................................................... 36 

6.1.3 

Composting ............................................................................................................... 39 

6.1.4 

Treatment (Recovery)............................................................................................... 39 

6.1.5  Disposal ..................................................................................................................... 40 

6.2  Approach to Modelling Waste Imports and Exports .................................................... 41 

6.2.1 

Summary of the Export Tool .................................................................................... 42 

6.2.2 

Case Study: Exports from United Kingdom to the Netherlands ............................ 47 

Implications of Excluding Imports/Exports of Residual Waste / RDF from the 

6.2.3 
Municipal Waste Model......................................................................................................... 51 

6.3 

Improving Reporting on Imports and Exports of MSW ................................................ 52 

6.3.1  Definition of Municipal Solid Waste ........................................................................ 54 

6.3.2 

Tracking Municipal Waste Movements – Issues with Mixing and Re-export....... 56 

6.3.3 

Setting up a Legal Reporting Framework ............................................................... 57 

7.0 

Updates to the Municipal Waste Model ............................................................ 59 

7.1  General Structural Changes ............................................................................................ 59 

7.2  User Interface .................................................................................................................. 59 

7.3 

Interactive Tools .............................................................................................................. 61 

7.4  Model Guidance .............................................................................................................. 63 

8.0 

9.0 

Dissemination of the Results ............................................................................ 67 

Training and Technical Support ......................................................................... 68 

LIST OF APPENDICES .................................................................................................... 69 

A.1.0  C&D Model Overview .................................................................................................. 69 

A.2.0  C&D Waste Model – Member State Summary Reports ............................................ 69 

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A.3.0  Municipal Waste Model – Member State Summary Reports................................... 69 

A.4.0 

Log of Actions Taken on the Municipal Waste Model .............................................. 69 

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List of Tables, Figures and Boxes 

Table 2-1: Summary of Key Changes to the Municipal Waste Model ......................................... 4 
Table 2-2: Comparison of Costs - Option 3.1-High vs Full Implementation1)2 ............................ 7 

Figure 2-1: 65% Preparation for Reuse and Recycling Target vs Full Implementation  – Change 
in Final Management Destinations (EU28)............................................................................. 8 

Figure 2-2: 65% Preparation for Reuse and Recycling Target vs Full Implementation  – 

Financial Costs (EU28).............................................................................................................. 9 

Figure 2-3: 65% Preparation for Reuse and Recycling Target vs Full Implementation – 

Environmental Externalities (EU28) ...................................................................................... 10 

Figure 2-4: 65% Preparation for Reuse and Recycling Target vs Full Implementation – Net 

Social Costs and Benefits (EU28)........................................................................................... 11 

Table 2-3: 65% Preparation for Reuse and Recycling Target vs Full Implementation – Net 
Social Costs and Benefits by Member State, Employment, and Greenhouse Gas 
Reduction ................................................................................................................................ 12 

Figure 2-5: 65% Preparation for Reuse and Recycling Target with Derogations vs Full 

Implementation – Change in Final Management Destinations (EU28) .............................. 13 

Figure 2-6: 65% Preparation for Reuse and Recycling Target with Derogations vs Full 

Implementation – Financial Costs (EU28) ............................................................................ 14 

Figure 2-7: 65% Preparation for Reuse and Recycling Target vs Full Implementation  – 

Environmental Externalities (EU28) ...................................................................................... 15 

Figure 2-8: 65% Preparation for Reuse and Recycling Target vs Full Implementation  – Net 

Social Costs and Benefits (EU28)........................................................................................... 16 

Table 2-4: 65% Preparation for Reuse and Recycling Target vs Full Implementation – Net 
Social Costs and Benefits by Member State, Employment, and Greenhouse Gas 
Reduction ................................................................................................................................ 16 

Table 2-5: Member State Specific Targets for 70% MSW Preparation for Reuse / Recycling 
with Varied Annual Progression (all Figures given as % of Total Municipal Waste 
Prepared for Reuse / Recycled)............................................................................................. 19 

Figure 2-9: Final Management Destinations of Waste in Adjusted 70% MSW Recycling 

Scenario Relative to Full Implementation, EU28, 2011-2035 ............................................... 0 

Figure 2-10: Financial Costs of Adjusted 70% MSW Recycling Scenario Relative to Full 

Implementation, EU28, 2012-2035......................................................................................... 1 

Figure 2-11: Environmental Costs of Adjusted 70% MSW Recycling Scenario Relative to Full 

Implementation, EU28, 2012-2035......................................................................................... 2 

Figure 2-12: Net Social Costs of Adjusted 70% MSW Recycling Scenario Relative to Full 

Implementation, EU28, 2012-2035......................................................................................... 3 

Table 2-6: 65% Preparation for Reuse and Recycling Target vs Full Implementation – Net 
Social Costs and Benefits by Member State, Employment, and Greenhouse Gas 
Reduction .................................................................................................................................. 3 

FINAL REPORT  

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Table 3-1: Parameters Included in Sensitivity Analysis with Upper and Lower Ranges ............ 5 

Figure 3-1: Variance in Social Cost of Waste Management in the EU28, under Full 

Implementation (NPV over 2015 – 2030 in 2015 Real Term Prices) .................................. 10 

Figure 3-2: Variance in Social Cost of Waste Management in the EU28, under Full 

Implementation (NPV over 2015 – 2030, % Change) .......................................................... 11 

Figure 3-3: Variance in Social Cost of Waste Management in the EU28, under Option 3.1-High 
(NPV over 2015 – 2030 in 2015 Real Term Prices) .............................................................. 12 

Figure 3-4: Variance in Social Cost of Waste Management in the EU28, under Option 3.1-High 
(NPV over 2015 – 2030, % Change) ...................................................................................... 13 

Figure 3-5: Variance in Social Cost of Waste Management in the EU28, Option 3.1-Hiogh 

Compared to Full Implementation (NPV over 2015 – 2030 in 2015 Real Term Prices) .... 14 

Figure 3-6: Variance in Social Cost of Waste Management in the EU28, Option 3.1-High 

Compared to Full Implementation (NPV over 2015 – 2030, % Change) ............................ 15 

Figure 4-1: Overview of the Construction and Demolition Waste Model ................................ 19 

Figure 4-2: Full Implementation vs Business as Usual – Change in Final Management (EU28)

 ................................................................................................................................................. 22 

Figure 4-3: Full Implementation vs Business as Usual – Change in Final Management by 2020

 ................................................................................................................................................. 23 

Figure 4-4: Full Implementation vs Business as Usual – Change in Employment by 2030 (Full 

Time Equivalent) .................................................................................................................... 24 

Figure 4-5: Full Implementation vs Business as Usual – Net Costs and Benefits (EU28) ......... 25 

Figure 4-6: Full Implementation vs Business as Usual – Net Costs and Benefits by Member 

State (NPV 2015-2035, 2015 Real Term Prices) ................................................................... 26 

Figure 4-7: More Ambitious vs Business as Usual – Change in Final Management (EU28) ..... 27 

Figure 4-8: More Ambitious vs Business as Usual – Change in Final Management by 2020 ... 28 

Figure 4-9: More Ambitious vs Business as Usual – Change in Employment by 2030 (Full Time 
Equivalent) .............................................................................................................................. 29 

Figure 4-10: More Ambitious vs Business as Usual – Net Costs and Benefits (EU28) .............. 30 

Figure 4-11: More Ambitious vs Business as Usual – Net Costs and Benefits by Member State 
(NPV 2015-2035, 2015 Real Term Prices)............................................................................. 31 

Table 6-1: Overview of Permissible Transfrontier Waste Shipments under the Waste 

Shipment Regulations (WSR)................................................................................................. 35 

Figure 6-1: Exports of Waste Plastics and Selected Waste Metals from EU Member States 

(1999 – 2011).......................................................................................................................... 37 

Figure 6-2: Eunomia’s Export Tool – Accounting for the Costs and Benefits of Exporting 

Waste for Treatment at Foreign Incinerators and/or MBT Plants ..................................... 45 

Figure 6-3: Overview of the Export Tool ..................................................................................... 46 

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Figure 6-4: Tonnes of RDF Exported from England and Wales to Europe between July 2010 

and July 2014 .......................................................................................................................... 48 

Table 6-2: Transport Costs for Exporting Waste from the UK to NL ......................................... 48 

Table 6-3: Net Cost to Society of Incinerating Waste in the UK vs Incineration in the 

Netherlands1 ........................................................................................................................... 49 
Table 6-4: Net Cost of Treating Waste in UK vs NL in Current Market1 .................................... 50 

Box 1: European Data Interchange for Waste Notification Systems (EUDIN) .......................... 53 

Figure 6-5: Overview of the EUDIN System................................................................................. 54 

Figure 6-6: Hypothetical Example of the Mixing and Movement of Waste Materials Sent for 

Recycling and the Assignment of EWC Codes ...................................................................... 57 

Figure 7-1: Setup Model Page ...................................................................................................... 60 

Figure 7-2: Waste Arisings Projections Page ............................................................................... 60 

Figure 7-3: Integrated Tool to Define Policy Scenarios .............................................................. 61 

Figure 7-4: Integrated Eurostat Data Conversion Tool ............................................................... 62 

Figure 7-5: Integrated Sensitivity Test Tool................................................................................. 62 

Figure 7-6: Integrated Waste Prevention Tool............................................................................ 63 

Figure 7-7: Example Guidance Included in the User Interface .................................................. 64 

Figure 7-8: Navigation Pane in the Calculations File .................................................................. 65 

Figure 7-9: Example of Flow Diagram with Hyperlinks............................................................... 65 

Figure 7-10: Example of Overview Flow Diagram ....................................................................... 66 

FINAL REPORT  

vii 

 
 
 
 
 
 
 
 
 
 
1.0 

Introduction 

Eunomia Research & Consulting (Eunomia) has been commissioned by DG Environment of 
the European Commission to further develop the European Reference Model on Municipal 
Waste Management and undertake additional analysis and reporting. This project, entitled 
‘Further Development of the European Reference Model on Waste Generation and 
Management’, is multifaceted and builds on previous work undertaken by Eunomia under 
the following two contracts: 

 
 

‘Development of a Modelling Tool on Waste Generation and Management’;1 and 
‘Impact Assessment on Options Reviewing Targets in the Waste Framework 
Directive’.2 

These projects have all been delivered under Eunomia’s framework contract with the 
European Commission on ‘Technological, Socio-Economic and Cost-Benefit Assessments 
Related to the Implementation and Further Development of EU Waste Legislation’.  

The current project brings together a number of strands of work which included the 
following: 

1)  Improving the usability of the European Reference Model on Municipal Waste 

Management (from now on referred to as the Municipal Waste Model) by developing 
a user interface and a number of additional integrated tools;  

2)  Providing training and support to help the European Environment Agency (EEA) and 
European Topic Centre on Waste Management and the Green Economy use the 
model;  

3)  Using the Municipal Waste Model to analyse three policy scenarios and to review 

how sensitive the model outputs are to changes in key input assumptions; 

4)  Developing a standalone C&D model; and 
5)  Producing summary reports for individual Member States.      

Given the varied objectives of this contract the structure of this Final Report does not follow 
a clear narrative as is typical of other studies. Instead, the results have been presented in a 
manner which is best suited to the Commission’s needs and their plans for disseminating the 
findings.  

1 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool 
on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment and European Environment Agency, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
2 Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-Institut (2014) Impact Assessment 
on Options Reviewing Targets in the Waste Framework Directive, Landfill Directive and Packaging and 
Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

FINAL REPORT  

1 

 
                                                   
 
The report covers the following with further detail being provided in a number of technical 
appendices:  

  Section 2.0 – summarises the key results of three additional policy scenarios which 

were modelled under this contract and compares how the results have changed since 
the publication of the Impact Assessment on the revision of the waste management 
targets3; 

  Section 3.0 – presents the results of the sensitivity tests that were conducted as part 
of this contract. These results demonstrate how sensitive the Municipal Waste Model 
is to changes in key input assumptions; 

  Section 4.0 – introduces the construction and demolition (C&D) waste model that 
was developed as part of this project and the results for two policy scenarios that 
were modelled using this model; 

  Section 5.0 – signposts readers to Appendix A.3.0 which is a standalone document 

that introduces key elements of the Municipal Waste Model. For each Member State 
it also identifies key assumptions that are included in the model and shows how, for 
a single scenario, the model systematically builds up the results based on 
environmental and financial costs; 

  Section 6.0 – addresses the complexities of including the import and export of 

municipal waste in the Municipal Waste Model and introduces the standalone Export 
Tool that was developed by Eunomia; 

  Section 7.0 – a number of structural changes were made to the Municipal Waste 

Model under this contract and these are summarised in this section;  

  Section 8.0 – describes how the results arising from this study were disseminated 

more widely; and 

  Section 9.0 – summarises the trainings sessions that were provided to the European 
Environment Agency and the European Topic Centre on Waste Management and the 
Green Economy.   

3 European Commission (2014) Impact Assessment Accompanying the Document: Proposal for Reviewing the 
European Waste Management Targets, July 2014, http://ec.europa.eu/environment/waste/target_review.htm 

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2.0  Results of Additional Model Simulations 

Through discussions with the Commission it was agreed that the following three scenarios 
would be modelled: 

  2030, 65% preparation for reuse and recycling target for MSW – Commission 

Decision 2011/753/EU allows Member States to report on their recycling rates using 
one of four different calculation methods.4 This scenario assumed that Member 
States will use their chosen method for the existing 2020 target. For the 2030 targets 
it is assumed that calculation method 4 will be used by all Member States (i.e. % of 
total MSW recycled). For this scenario no interim target in 2025 was modelled and it 
was assumed that no derogations would be issued.  

  2030, 65% preparation for reuse and recycling target for MSW with derogations – 
this scenario is identical to the one above, but it was assumed that Member States 
with recycling rates below 20% in 2013 – that is, Estonia, Greece, Croatia, Latvia, 
Malta, Romania, and Slovakia – would request a derogation which would allow them 
to achieve the 65% target in 2035.  

  New 70% MSW Recycling scenario – this scenario assumes an annual progression of 
3.0% for each Member State until 50% of MSW is prepared for reuse /recycled, 
thereafter it is assumed that progress falls to 2.5% per annum until 70% preparation 
for reuse and recycling is achieved (with recycling rates being measured by means of 
calculation method 4). 

In the sections below, as in the Impact Assessment, these scenarios are all compared against 
the Full Implementation scenarios. This scenario assumes that Member States achieve full 
compliance with the Waste Framework Directive and Landfill Directive Targets. This scenario 
is used as the baseline against which the new proposed targets have been compared (i.e. to 
allow for a comparison against what has already been agreed and set down by Member 
States in their national legislation). For a detailed look at this scenario refer to Section 8.2 of 
the final Targets Review Report.5 

Before discussing the results of each of the above scenarios it is worth summarising and 
examining the technical changes that have been made to the Municipal Waste Model since 
the results were generated for the Impact Assessment which reviewed the European waste 
management targets in 2014.6  

4 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
5 Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-Institut (2014) Impact Assessment 
on Options Reviewing Targets in the Waste Framework Directive, Landfill Directive and Packaging and 
Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 
6 European Commission (2014) Impact Assessment Accompanying the Document: Proposal for Reviewing the 
European Waste Management Targets, July 2014, http://ec.europa.eu/environment/waste/target_review.htm 

FINAL REPORT  

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2.1  Changes to the Model 

As part of this contract the Municipal Waste Model has undergone both technical and 
structural changes. In this context technical changes refer to changes which will have altered 
the final outputs being generated by the model (in most cases these changes have been 
minimal), whilst the structural changes refer to improvements to the model to make it more 
user friendly but which have no bearing on the actual outputs of the model (e.g. the addition 
of a user interface). This section deals exclusively with the technical changes that have been 
made to the model, the structural changes that have been made are described in Section 
7.0.  

The key technical changes that have been made to the model are summarised in Table 2-1. It 
is important to note that the updated model has been used to produce the results which are 
presented in this section. We therefore also provide a rough indication of how the individual 
changes will have altered the results since the model was used to run the scenarios for the 
Impact Assessment in 2014. The impact of these changes on the model outputs are 
discussed below.  

Table 2-1: Summary of Key Changes to the Municipal Waste Model  

Key Changes to the Municipal Waste Model 

Given changes in the market for secondary materials over 
the last couple of years the material revenues for dry 
recyclables were updated. The changes were not 
substantial and are based on the average market price 
over the last two years. Further details on the updated 
prices can be found in Section 4.4 of Appendix A.3.0 
(including details of how they were calculated).   

Changed datasets used for the labour cost ratios following 
comments from the EEA – harmonised datasets in the 
model using the hourly rate data from Eurostat, rather 
than mean net annual earnings.7  

Switched from the EU28 deflators to country specific 
deflators which are used to adjust some of the landfill and 
other taxes. 

All costs have been updated to 2015 real terms prices 
based on country specific deflators. 

Impact on the Results/Outputs Relative to the 
Version of the Model used for the Impact 
Assessment  

Given the fall in commodity prices over the last 
couple of years the assumed revenues derived 
from secondary materials in the Municipal Waste 
Model have, for the most part, been reduced 
slightly. This update has meant that the amount 
of revenue derived from the sale of recyclables is 
lower and thus the net cost of collecting dry 
recyclables is slightly higher.  
The labour cost ratios will have changed for all 
Member States marginally affecting the labour 
costs in treatment plants and in waste collection 
services. This appears to have had a minimal 
effect on the results. 

Very slight changes to costs calculated. 

The outputs of both the financial and 
environmental modules will now be slightly 
different as the deflators have been updated. This 
change affects the magnitude of the results. As 
the value of money increases over time, moving 
from 2013 to 2015 prices will increase the costs 
or benefits, depending on the outcomes of the 
scenarios. 

7 Eurostat: Labour cost levels [lc_lci_lev], 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lc_lci_lev&lang=en 

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Key Changes to the Municipal Waste Model 

In the first impact assessment the Net Present Value 
(NPV) of all scenarios was compared based on the period 
2014 to 2030. In this contract we considered two 
scenarios which extend out to 2035. It was therefore 
necessary to extend the NPV calculations out to 2035.    

Adjusted employment intensity factors in light of new 
information.  
The original model included a ‘goal seek’ function to pin 
Member State recycling and landfilling rates to the 
recycling target /landfill diversion target which had been 
set as part of the scenarios being modelled. This goal seek 
function was accurate to within ±1%. The functionality 
has been improved so that the model does not step by % 
point increments, and therefore is more accurate. 

Some aspects of the collections module have been 
updated to account more accurately for differences in 
collecting materials between a shared service (i.e. flats) 
and individual houses (i.e. door-to-door).    

The approach to calculating the cost of operation civic 
amenity sites (container parks) has been improved. 
Instead of calculating a single per household cost, the 
model now calculates the following element separately: 
1) investment costs, 2) labour costs and 3) other 
operational costs per tonne of throughput. 
The calculation method chosen by Member States for 
reporting performance against the existing 50% recycling 
target was updated for Denmark and the Netherlands as 
new information was made available to the European 
Commission (Denmark is now using method 1 and the 
Netherlands is using method 2). 
The assumed composition of MSW has been updated for 
Lithuania because the country assumed that scrap metal 
was included in the municipal waste stream. The metal 
content of the waste stream was therefore very high and 
skewing the results.  

Impact on the Results/Outputs Relative to the 
Version of the Model used for the Impact 
Assessment  

Extending the NPV calculation beyond 2030 has 
no material impact on the results but does affect 
the magnitude of the figures as they are reported. 
Because an additional five years of costs and 
benefits are added, there is an associated 
increase/decrease in the final reported NPV 
figures. 
Slight changes in the employment impacts of 
individual scenarios. 

This change will reduce the generation of 
anomalous results for Member States who are 
already very close to achieving the target 
recycling rate set out in a given policy scenario. 
For some countries the results will have changed 
by up to 1%. 

The extent of the change varies from country to 
country, depending on the proportion of the 
housing stock which is made up of buildings with 
more than 10 households each, and therefore, 
are assumed to utilise shared collection services. 
This change limits the capture from shared 
properties. The overall effect has been to 
increase the costs of waste collection.  

The overall effect had been to increase the costs 
of waste management, though it should be noted 
that the model drives Member States towards a 
high density of CA site provision that might prove 
difficult to achieve in practice in many situations.  

This change has had a relatively minor impact on 
the EU-28 results.  

This appears to have had a very minimal effect on 
the EU-28 results.  

For a single scenario Table 2-2 compares the results between those generated for the Impact 
Assessment and those generated using the updated Municipal Waste Model. This 
comparison is intended to provide an indication of the extent to which the model outputs 
have changed as a result of the further development and enhancement of the Municipal 

FINAL REPORT  

5 

 
 
Waste Model under this contract. For comparison purposes we have used Option 3.1-High 
from the Impact Assessment.8 This scenario assumes that Member States will achieve 50% 
recycling by their chosen calculation method in 2020, and then 60% and 70% recycling by 
method 4 in 2025 and 2030, respectively.  

The results for the Impact Assessment were produced in 2013 prices. In Table 2-2 we 
therefore compare the Net Present Value (NPV) results between the initial Impact 
Assessment and the updated model in 2013 prices.9 We also show the results produced by 
the updated Municipal Waste Model in 2015 prices to show the impact that price inflation 
has had on the results. It can be seen that external costs (i.e. monetised environmental 
costs) have reduced in the updated Municipal Waste Model, falling by about 27% relative to 
the results reported in the Impact Assessment (i.e. negative values represent a cost saving 
and/or benefit to society; thus, the new mode outputs suggest that there is a greater net 
benefit to society). Conversely, the financial costs have increased, reducing the overall 
financial savings by 38% (if comparing the model results in 2013 real terms prices). The net 
position, however, remains largely unchanged with the net social cost only having shifted by 
5%.   

8 See European Commission (2014) Impact Assessment Accompanying the Document: Proposal for Reviewing 
the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm; alternatively, see Option 3.1.c in Eunomia 
Research & Consulting, Copenhagen Resource Institute, and Öko-Institut (2014) Impact Assessment on Options 
Reviewing Targets in the Waste Framework Directive, Landfill Directive and Packaging and Packaging Waste 
Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 
9 The Net Present Value is the current value of a stream of future payments, in this case discounted at the 
social discount rate of 4% (as agreed with the European Commission). 

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Table 2-2: Comparison of Costs - Option 3.1-High vs Full Implementation1)2 

Model Version / 
Model Variations 

External 
Costs 

Financial 
Costs 

Net Social 
Costs3 

Employment 

Greenhouse Gas Reduction 

Net Present Value (NPV) 

1,000 FTEs 

Million Tonnes CO2 eq 

First Impact Assessment (IA) Model 

NPV 2014 to 2030, € 
Billion, 2013 Prices 

Updated Model 

NPV 2015 to 2030, € 
Billion, 2015 Prices 
NPV 2015 to 2035, € 
Billion, 2015 Prices 

Notes: 

-€8.49 

-€8.41 

-€16.91 

138 

In 2030:  -39  

-€10.90 

-€5.38 

-€16.28 

115 

In 2030:  -36 

In 2035: 

2014 to 2030:  
-214 

2015 to 2030: 
-223 
2015 to 2035: 
- 

1.  See the following report for more details on Option 3.1.c and the analysis that was undertaken for 
the impact assessment: Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, 
Landfill Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.
pdf. 

2.  Negative costs represent a benefit to society. All scenarios compared against the Full 

Implementation. 

3.  Net social costs = financial costs + external costs. 

While the relative financial and external costs change by between 27% and 38%, this change 
should be viewed in terms of the absolute figures for the scenarios. The absolute cost of 
Option 3.1-High is in the order of €400 billion, far greater than the net changes reported in 
Table 2-2. The overall change between the models in absolute terms is therefore less than 
1% of the overall costs. It is clear that the results still show the same principles and allows 
for the same conclusions to be drawn, even after the model improvements have been made. 
In essence, there are still significant environmental benefits and financial savings to be 
gained by transitioning to 70% preparation for reuse and recycling in 2030.  

2.2  65% Preparation for Reuse and Recycling Target 

2.2.1  Change in Final Management Destinations 

Figure 2-1 shows that compared to the Full Implementation scenario this 65% target will 
lead to an 18% increase in recycling rates across the EU28 between 2020 and 2030. 
Intuitively one would expect to see a 15% increase in recycling rates between 2020 and 2030 
as the target rises from 50% to 65%. The greater than 15% increase is directly attributable to 
the fact that there is no consistent measurement method being applied for calculating the 
2020 recycling target in the Waste Framework Directive.  

FINAL REPORT  

7 

 
 
 
 
 
 
Figure 2-1: 65% Preparation for Reuse and Recycling Target vs Full 
Implementation – Change in Final Management Destinations (EU28) 

The increased recycling rates result in a corresponding decrease in the amount of residual 
waste requiring treatment and/or disposal. Across the EU28 landfilling and incineration are 
both shown to decrease by more than 6% by the time 65% recycling is achieved in 2030. The 
mass loss line represents losses from MBT processes, the use of which is also reduced under 
this scenario as materials are driven towards recycling.10 These effects occur because in 
some countries, investments in incineration and MBT are made in the Full Implementation 
scenario, so the higher target effectively forestalls some of the investment in incineration 
and MBT in these countries. 

2.2.2 

Financial Costs  

A breakdown of the financial costs of this scenario, relative to Full Implementation, is 
presented in Figure 2-2. From this it can be seen that across the EU28 there are net cost 
savings to be gained from this option (indicated by negative cost values). There are two 
competing costs: one from the increase in the cost of recycling and biowaste treatment, and 
the other from the avoided costs of waste being collected and treated as residual waste. In 
this scenario the former is always lower than the latter and hence there are net savings to be 
gained from this scenario. 

10 Here the negative mass loss shows that, relative to Full Implementing, evaporative/oxidative losses are less 
as a result of smaller volumes of material passing through MBT facilities.    

8 

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-10%-8%-6%-4%-2%0%2%4%6%8%10%12%14%16%18%20%2011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Change in Final Management Destinations, %RecyclingIncinerationLandfillMass Loss 
 
 
                                                   
 
It is important to understand the changes which the model is effectively displaying in this 
scenario. The modelling assumes that in the Full Implementation scenario, many countries 
have already had to invest significantly in the upgrading of collection services relative to the 
situation they were in in 2011 (the latest year for which data was available at the time the 
model was developed). In moving to higher recycling rates, effectively, the capture of 
materials for recycling increases, reducing (relative to the Full Implementation scenario) the 
quantity of residual waste requiring collection. The refuse collection service is modelled as 
undergoing two changes: first, the collection frequency falls; second, the refuse collection is 
charged for (i.e. pay as you throw is implemented). The combined effect of these changes to 
refuse collection and the (related) increases in the capture of materials for recycling is that, 
with relatively small changes in the cost of delivering the recycling collection service, the 
revenue generated from the sale of materials increases (so the costs, net of revenue 
generation, decline). At the same time, the reduced frequency of collection of refuse leads 
to savings on the delivery of the refuse collection service. In summary, the effect of 
measures which encourage / incentivise the use of the services for recycling is to improve 
the efficiency of the logistics, and capture more material for recycling from each household. 
This explains the effect on collection costs in this and other high recycling scenarios 
described in this chapter.   

Figure 2-2 shows that costs continue to change after 2030 and this is due to the fact that 
waste arisings continue to grow beyond this point. The amount of waste generated in most 
countries is expected to increase over time, meaning that there are greater volumes of 
waste that need to be collected and processed. This obviously requires greater financial 
investment in collecting, processing and treating the additional waste.   

Figure 2-2: 65% Preparation for Reuse and Recycling Target vs Full 
Implementation – Financial Costs (EU28) 

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

FINAL REPORT  

9 

-€8,000-€6,000-€4,000-€2,000€0€2,000€4,000€6,0002011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Financial Costs, Million EUR 2015 Real TermsResidual Waste Collection CostsRecycling Collection CostsLandfill CostsMBT CostsIncineration CostsOrganic Treatment CostsWaste Prevention CostsNet Costs 
 
2.2.3  Environmental Costs 

The majority of the environmental benefits are associated with the avoided greenhouse gas 
(GHG) emissions related to recycling and the avoidance of residual waste treatment and 
disposal (Figure 2-3). The benefits outweigh the additional emissions to air that are 
generated as a result of the treatment of biowaste and the collection of recyclables.  

Figure 2-3 shows that the benefits continue to accrue after the 60% recycling target has 
been achieved in 2030. This is because of the way that emissions from landfill are accounted 
for and the fact the damage costs for greenhouse gases are assumed to increase over time. 
Waste landfilled in one year will continue to emit methane for a number of years afterwards. 
Thus, avoided landfilling under this and subsequent Options means that the environmental 
benefits continue to improve beyond 2030. In this sense the environmental benefits are 
different to the financial costs which stabilise once the target is met in 2030. 

Figure 2-3: 65% Preparation for Reuse and Recycling Target vs Full 
Implementation – Environmental Externalities (EU28) 

Note: Positive external costs denote a cost to society whilst negative costs represent a benefit. 

2.2.4  Net Social Costs and Employment 

With both the financial and environmental costs proving to be favourable relative to Full 
Implementation, the net position of this scenario is also favourable. The results depicted in 
Figure 2-4 show that by 2035 the net social cost may be reduced by up to €5 billion per year 
in 2015 real term prices.  

10 

28/05/2015 

-€5,000-€4,000-€3,000-€2,000-€1,000€0€1,0002011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Externalities, Million EUR 2015 Real TermsCollection & sorting - AQCollection & sorting - GHGsLandfill - AQ + OtherLandfill - GHGsIncineration - AQ + OtherIncineration - GHGsMBT etc - AQ + OtherMBT etc - GHGsOrganic Treatment - AQ + OtherOrganic Treatment - GHGsDry Recycling - AQ + OtherDry Recycling - GHGsWaste Prevention - AQ + OtherWaste Prevention - GHGsNet Externalities 
 
 
Figure 2-4: 65% Preparation for Reuse and Recycling Target vs Full 
Implementation – Net Social Costs and Benefits (EU28) 

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

With a view of the net social costs across all Member States, it is evident that under this 
scenario all Member States, other than Malta, Poland and Romania, experience a net social 
benefit (Table 2-3). For the EU28 as a whole the NPV (2015-2035) shows a net benefit of 
€25.56 billion in 2015 real term prices. 

The employment intensities associated with the collection and processing of recyclables is 
typically much higher than those for residual waste collections and treatment/disposal. It is 
therefore of little surprise that this scenario leads to an increase in employment as greater 
quantities of waste are sent for recycling (Table 2-3With a view of the net social costs across 
all Member States, it is evident that under this scenario all Member States, other than Malta, 
Poland and Romania, experience a net social benefit (Table 2-6). For the EU28 as a whole the 
NPV (2015-2035) shows a net benefit of €45.53 billion in 2015 real term prices. This is 
substantially higher than the scenarios above because of the higher recycling target and 
because the financial savings and environmental benefits are realised much earlier (meaning 
that they are not as heavily discounted).   

The estimated increase in direct employment is 117 thousand FTEs across the EU28 by 2035. 
This is higher than the rate achieved under the 65% recycling targets discussed above 
because a greater volume of material will be sent for recycling (which is more labour 
intensive than was disposal or incineration).   

Table 2-6). The extent to which these job opportunities will be realised in Europe depends 
on the amount of waste that is processed within the European Union’s borders as opposed 
to being exported for treatment abroad. The estimated increase in direct employment is 104 

FINAL REPORT  

11 

-€6,000-€5,000-€4,000-€3,000-€2,000-€1,000€0€1,0002011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Costs, Million EUR 2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
thousand FTEs across the EU28 by 2035. No provision was given for possible multiplier 
effects. 

Table 2-3: 65% Preparation for Reuse and Recycling Target vs Full 
Implementation – Net Social Costs and Benefits by Member State, Employment, 
and Greenhouse Gas Reduction 

Financial 
Costs 

External 
Costs 

Net Social 
Costs 

Employment 

Greenhouse Gas Reduction 

Member State 

Austria 
Belgium 
Bulgaria 
Croatia 
Cyprus 
Czech Republic 
Denmark 
Estonia 
Finland 
France 
Germany 
Greece 
Hungary 
Ireland 
Italy 
Latvia 
Lithuania 
Luxembourg 
Malta 
Netherlands 
Poland 
Portugal 
Romania 
Slovakia 
Slovenia 
Spain 
Sweden 
United Kingdom 
EU28 

NPV 2015-2035, € Billion 2015 Real 
Term Prices 

1,000 FTEs 
in 2035 

-0.25 
-0.11 
-0.01 
-0.10 
-0.09 
-0.14 
-0.19 
0.00 
-0.05 
-2.77 
-0.70 
0.07 
0.06 
-0.22 
-4.07 
0.00 
0.06 
-0.01 
0.02 
-0.28 
0.79 
0.20 
0.85 
0.04 
0.01 
-0.69 
-0.12 
-0.12 
-7.82 

-0.21 
-0.23 
-0.12 
-0.20 
-0.06 
-0.36 
-0.07 
-0.04 
-0.06 
-4.24 
-0.33 
-0.33 
-0.52 
-0.20 
-3.36 
-0.03 
-0.12 
-0.01 
-0.01 
-0.29 
-0.52 
-0.41 
-0.70 
-0.21 
-0.05 
-0.65 
-0.12 
-2.28 
-15.74 

-0.46 
-0.34 
-0.13 
-0.30 
-0.15 
-0.50 
-0.26 
-0.04 
-0.11 
-7.01 
-1.04 
-0.26 
-0.46 
-0.42 
-7.44 
-0.03 
-0.06 
-0.02 
0.00 
-0.56 
0.27 
-0.21 
0.14 
-0.17 
-0.04 
-1.34 
-0.24 
-2.40 
-23.56 

1.3 
0.8 
0.4 
2.6 
0.3 
1.7 
0.7 
0.3 
0.8 
21.1 
1.6 
1.9 
3.0 
1.3 
18.0 
0.2 
0.7 
0.0 
0.1 
2.0 
11.2 
3.5 
2.3 
1.0 
0.2 
5.8 
0.5 
20.5 
104.0 

Million 
Tonnes CO2 eq 
in 2035 
-0.46 
-0.18 
-0.29 
-0.48 
-0.17 
-0.81 
-0.07 
-0.12 
-0.12 
-6.47 
-0.54 
-0.85 
-1.15 
-0.75 
-6.87 
-0.07 
-0.33 
-0.02 
-0.04 
-0.47 
-1.55 
-1.12 
-1.70 
-0.48 
-0.10 
-1.61 
-0.14 
-4.62 
-31.59 

Million Tonnes 
CO2 eq, 2015-
2035 
-4.75 
-1.83 
-3.06 
-4.77 
-1.79 
-8.25 
-0.68 
-1.20 
-1.23 
-66.70 
-5.68 
-8.72 
-11.76 
-7.37 
-67.71 
-0.74 
-3.50 
-0.15 
-0.42 
-4.75 
-16.01 
-11.30 
-17.86 
-4.65 
-1.05 
-16.67 
-1.39 
-48.61 
-322.59 

2.3  65% Preparation for Reuse and Recycling Target with 

Derogations 

2.3.1  Change in Final Management Destinations 

One would expect minimal differences between this scenario and the one above which 
assumes that no derogations will be granted for the 2030 target. The only difference is that 
the inclusion of derogations will results in a slight delay in the rate at which the 
environmental and financial benefits occur. From Figure 2-5 it can be seen that - assuming 

12 

28/05/2015 

 
 
that Estonia, Greece, Croatia, Latvia, Malta, Romania, and Slovakia apply for derogations 
until 2035 – recycling rates continue to rise after 2030, with a corresponding decrease in the 
volume of residual waste requiring treatment. The end position in 2035, however, is 
identical to that achieved in 2030 in the above scenario which does not take derogations 
into account. This delay in the implementation of the final 65% target is what leads to a 
slower realisation of the financial savings and environmental benefits.      

Figure 2-5: 65% Preparation for Reuse and Recycling Target with Derogations 
vs Full Implementation – Change in Final Management Destinations (EU28) 

2.3.2  Financial Costs  

A breakdown of the financial costs of this scenario, relative to Full Implementation, is 
presented in Figure 2-6. When comparing this figure to the financial costs for the scenario 
without derogations (see Figure 2-2) it is clear that there is a very slight delay in the financial 
savings as the countries with derogations continue to improve their recycling performance 
after 2030.  

FINAL REPORT  

13 

-10%-8%-6%-4%-2%0%2%4%6%8%10%12%14%16%18%20%2011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Change in Final Management Destinations, %RecyclingIncinerationLandfillMass Loss 
 
 
 
Figure 2-6: 65% Preparation for Reuse and Recycling Target with Derogations 
vs Full Implementation – Financial Costs (EU28) 

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

2.3.3  Environmental Costs 

By 2035 both this scenario and the one above have achieved the same end point with net 
environmental benefits exceeding €4.5 billion per annum in 2015 real term prices (Figure 
2-7). When derogations for the 65% preparation for reuse and recycling target are given the 
net environmental benefits achieved before 2030 are slightly less. However, this is made up 
for by the fact that the benefits end up being accrued after 2030 which means that both 
scenarios ultimately reach the same net position. 

14 

28/05/2015 

-€8,000-€6,000-€4,000-€2,000€0€2,000€4,000€6,0002011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Financial Costs, Million EUR 2015 Real TermsResidual Waste Collection CostsRecycling Collection CostsLandfill CostsMBT CostsIncineration CostsOrganic Treatment CostsWaste Prevention CostsNet Costs 
 
Figure 2-7: 65% Preparation for Reuse and Recycling Target vs Full 
Implementation – Environmental Externalities (EU28) 

Note: Positive external costs denote a cost to society whilst negative costs represent a benefit. 

2.3.4  Net Social Costs and Employment 

With both the financial and environmental costs proving to be favourable relative to Full 
Implementation, the net position of this scenario is also favourable (Figure 2-8). The results 
depicted in this figure show that by 2035 the net social cost may be reduced by up to €5 
billion per year (in 2015 real term prices).  

FINAL REPORT  

15 

-€5,000-€4,000-€3,000-€2,000-€1,000€0€1,0002011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Externalities, Million EUR 2015 Real TermsCollection & sorting - AQCollection & sorting - GHGsLandfill - AQ + OtherLandfill - GHGsIncineration - AQ + OtherIncineration - GHGsMBT etc - AQ + OtherMBT etc - GHGsOrganic Treatment - AQ + OtherOrganic Treatment - GHGsDry Recycling - AQ + OtherDry Recycling - GHGsWaste Prevention - AQ + OtherWaste Prevention - GHGsNet Externalities 
 
 
Figure 2-8: 65% Preparation for Reuse and Recycling Target vs Full 
Implementation – Net Social Costs and Benefits (EU28)

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

With a view of the net social costs across all Member States, it is evident that under this 
scenario all Member States, other than Malta, Poland and Romania, experience a net social 
benefit (Table 2-4). For the EU28 as a whole the NPV (2015-2035) shows a net benefit of 
€23.10 billion in 2015 real term prices. This is a smaller benefit than recoded under the 
above scenario where no derogations were considered (i.e. NPV of €25.56 billion). The Net 
Present Value is the current value of a stream of future payments, in this instance 
discounted at the social discount rate of 4% per annum (as agreed with the European 
Commission). This means that financial follows which occur later in time are more heavily 
discounted which explains why the issuing of derogations will results in a lower NPV.   

The estimated increase in direct employment is 104 thousand FTEs across the EU28 by 2035. 
Given that by 2035 there is no material difference between this scenario and the one above 
these figures would be expected to be identical. 

Table 2-4: 65% Preparation for Reuse and Recycling Target vs Full 
Implementation – Net Social Costs and Benefits by Member State, Employment, 
and Greenhouse Gas Reduction 

Member State 

Austria 
Belgium 
Bulgaria 

16 

Financial 
Costs 

External 
Costs 

Net Social 
Costs 

Employment 

Greenhouse Gas Reduction 

NPV 2015-2035, € Billion 2015 Real 
Term Prices 

1,000 FTEs 
in 2035 

-0.25 
-0.11 
-0.01 

-0.21 
-0.23 
-0.12 

-0.46 
-0.34 
-0.13 

1.3 
0.8 
0.4 

Million 
Tonnes CO2 eq 
in 2035 
-0.46 
-0.18 
-0.29 

Million 
Tonnes CO2 eq, 
2015-2035 
-4.75 
-1.83 
-3.06 

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-€6,000-€5,000-€4,000-€3,000-€2,000-€1,000€0€1,0002011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Costs, Million EUR 2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Member State 

Croatia 
Cyprus 
Czech Republic 
Denmark 
Estonia 
Finland 
France 
Germany 
Greece 
Hungary 
Ireland 
Italy 
Latvia 
Lithuania 
Luxembourg 
Malta 
Netherlands 
Poland 
Portugal 
Romania 
Slovakia 
Slovenia 
Spain 
Sweden 
United Kingdom 
EU28 

Financial 
Costs 

External 
Costs 

Net Social 
Costs 

Employment 

Greenhouse Gas Reduction 

NPV 2015-2035, € Billion 2015 Real 
Term Prices 

1,000 FTEs 
in 2035 

-0.06 
-0.09 
-0.14 
-0.19 
0.00 
-0.05 
-2.77 
-0.70 
0.12 
0.06 
-0.22 
-4.07 
0.00 
0.06 
-0.01 
0.02 
-0.28 
0.79 
0.20 
0.83 
0.06 
0.01 
-0.69 
-0.12 
-0.12 
-7.72 

-0.16 
-0.06 
-0.36 
-0.07 
-0.03 
-0.06 
-4.24 
-0.33 
-0.25 
-0.52 
-0.20 
-3.36 
-0.02 
-0.12 
-0.01 
-0.01 
-0.29 
-0.52 
-0.41 
-0.54 
-0.16 
-0.05 
-0.65 
-0.12 
-2.28 
-15.38 

-0.22 
-0.15 
-0.50 
-0.26 
-0.02 
-0.11 
-7.01 
-1.04 
-0.12 
-0.46 
-0.42 
-7.44 
-0.02 
-0.06 
-0.02 
0.01 
-0.56 
0.27 
-0.21 
0.30 
-0.11 
-0.04 
-1.34 
-0.24 
-2.40 
-23.10 

2.6 
0.3 
1.7 
0.7 
0.3 
0.8 
21.1 
1.6 
1.9 
3.0 
1.3 
18.0 
0.2 
0.7 
0.0 
0.1 
2.0 
11.2 
3.5 
2.3 
1.0 
0.2 
5.8 
0.5 
20.5 
104.0 

Million 
Tonnes CO2 eq 
in 2035 
-0.48 
-0.17 
-0.81 
-0.07 
-0.12 
-0.12 
-6.47 
-0.54 
-0.85 
-1.15 
-0.75 
-6.87 
-0.07 
-0.33 
-0.02 
-0.04 
-0.47 
-1.55 
-1.12 
-1.70 
-0.48 
-0.10 
-1.61 
-0.14 
-4.62 
-31.59 

Million 
Tonnes CO2 eq, 
2015-2035 
-3.63 
-1.79 
-8.25 
-0.68 
-0.93 
-1.23 
-66.70 
-5.68 
-6.60 
-11.76 
-7.37 
-67.71 
-0.57 
-3.50 
-0.15 
-0.32 
-4.75 
-16.01 
-11.30 
-13.90 
-3.65 
-1.05 
-16.67 
-1.39 
-48.61 
-313.83 

2.4  New 70% MSW Recycling Target 

The New 70% MSW Recycling scenario is based on a progressive increase in the preparation 
for reuse / recycling rate of each Member State, with the 2013 recycling rate acting as a 
baseline (as reported to Eurostat).11 The only exception to this is Romania which reported a 
recycling rate of 2.55% in 2013. It has been reported by the European Environment Agency 
that: 

“Romania only includes recycled packaging waste from households to a limited extent 
in the reporting of MSW recycled.”12 

11 Eurostat (2015) Municipal Waste [env_wasmun], Date Accessed: 23 June 2015, Downloaded from: 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasmun&lang=en 
12 European Environment Agency (2013) Municipal Waste Management in Romania, February 2013, 
www.eea.europa.eu/publications/managing-municipal-solid-waste 

FINAL REPORT  

17 

 
 
                                                   
 
In addition, the reported recycling rate almost certainly does not take into account material 
which has been recycled via the informal sector. A report by BiPro notes that in Romania:  

“The participation of the informal sector is still very significant and takes into account 
collection of the valuable recyclables which can be sold on the market from landfills 
and industrial areas. […] Direct collection and trade of recyclables is the main source 
of income for the significant portion of the poor population in the cities (~40,000 
people).”13 

The Eurostat MSW recycling rate for Romania is therefore likely to be substantially 
underestimating the actual level of recycling. It was therefore assumed that the baseline 
recycling rate was 10% which is likely to a conservative estimate.  

Where the rate of progression is slower than under the Full Implementation scenario it has 
been assumed that Member States follow the Full Implementation recycling trajectory 
before starting with the stated progression rates. The progression rates for each country are 
shown in Table 2-5. It is clear that some Member States will achieve 70% recycling much 
sooner than others. For example, under this scenario it is expected that Germany will be 
recycling or preparing for reuse 70% of all municipal waste by 2016, compared to Romania 
who will only be expected to achieve this rate by 2035.  

In the scenarios above Member States were permitted to vary in their approach to 
measurement of the 2020 target by one of four methods. 14 In this scenario, the annual 
increase in recycling rates removes the need for this variation, and so recycling performance 
is measured consistently – using calculation Method 4 – across all target years. 

13 BiPro (2011) Country Factsheet Romania (RO), Report for DG Environment at the European Commission, 
http://ec.europa.eu/environment/waste/framework/pdf/RO_factsheet_FINAL.pdf  
14 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying Compliance with 
the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the Council, Decision 
2011/753/EU, http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 

18 

28/05/2015 

 
                                                   
 
Table 2-5: Member State Specific Targets for 70% MSW Preparation for Reuse / Recycling with Varied Annual Progression 
(all Figures given as % of Total Municipal Waste Prepared for Reuse / Recycled)   

3.0% annual increase from 2013 baseline until 50% recycling rate achieved, thereafter progress at 2.5% per annum 

Member State 

1
3
1
0
2

4
1
0
2

5
1
0
2

6
1
0
2

7
1
0
2

8
1
0
2

9
1
0
2

0
2
0
2

1
2
0
2

2
2
0
2

3
2
0
2

4
2
0
2

5
2
0
2

6
2
0
2

7
2
0
2

8
2
0
2

9
2
0
2

0
3
0
2

1
3
0
2

2
3
0
2

3
3
0
2

4
3
0
2

5
3
0
2

Austria 

Belgium 
Bulgaria2 
Croatia 

Cyprus 

56.1 

58.6 

61.1 

63.6 

66.1 

68.6 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

55.0 

57.5 

60.0 

62.5 

65.0 

67.5 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

28.5 

31.6 

34.7 

37.8 

40.8 

43.9 

47.0 

50.1 

52.6 

55.1 

57.6 

60.1 

62.6 

65.1 

67.6 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

14.9 

17.9 

20.9 

23.9 

26.9 

29.9 

32.9 

35.9 

38.9 

41.9 

44.9 

47.9 

50.9 

53.4 

55.9 

58.4 

60.9 

63.4 

65.9 

68.4 

70.0 

70.0 

70.0 

21.4 

24.4 

27.4 

30.4 

33.4 

36.4 

39.4 

42.4 

45.4 

48.4 

51.4 

53.9 

56.4 

58.9 

61.4 

63.9 

66.4 

68.9 

70.0 

70.0 

70.0 

70.0 

70.0 

Czech Republic 

24.2 

27.2 

30.2 

33.2 

36.2 

39.2 

42.2 

45.2 

48.2 

51.2 

53.7 

56.2 

58.7 

61.2 

63.7 

66.2 

68.7 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

Denmark 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Ireland 

Italy 
Latvia2 
Lithuania 

Luxembourg 
Malta2 
Netherlands 

Poland 

Portugal 

44.3 

47.3 

50.3 

52.8 

55.3 

57.8 

60.3 

62.8 

65.3 

67.8 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

17.4 

20.4 

23.4 

26.4 

29.4 

32.4 

35.4 

38.4 

41.4 

44.4 

47.4 

50.4 

52.9 

55.4 

57.9 

60.4 

62.9 

65.4 

67.9 

70.0 

70.0 

70.0 

70.0 

32.5 

35.5 

38.5 

41.5 

44.5 

47.5 

50.5 

53.0 

55.5 

58.0 

60.5 

63.0 

65.5 

68.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

37.6 

40.6 

43.6 

46.6 

49.6 

52.6 

55.1 

57.6 

60.1 

62.6 

65.1 

67.6 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

64.5 

67.0 

69.5 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

19.3 

22.3 

25.3 

28.3 

31.3 

34.3 

37.3 

40.3 

43.3 

46.3 

49.3 

52.3 

54.8 

57.3 

59.8 

62.3 

64.8 

67.3 

69.8 

70.0 

70.0 

70.0 

70.0 

26.4 

29.4 

32.4 

35.4 

38.4 

41.4 

44.4 

47.4 

50.4 

52.9 

55.4 

57.9 

60.4 

62.9 

65.4 

67.9 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

36.6 

39.6 

42.6 

45.6 

48.6 

51.6 

54.1 

56.6 

59.1 

61.6 

64.1 

66.6 

69.1 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

39.4 

42.4 

45.4 

48.4 

51.4 

53.9 

56.4 

58.9 

61.4 

63.9 

66.4 

68.9 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

16.9 

21.6 

26.4 

31.1 

35.8 

40.6 

45.3 

50.0 

52.5 

55.0 

57.5 

60.0 

62.5 

65.0 

67.5 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

27.8 

30.8 

33.8 

36.8 

39.8 

42.8 

45.8 

48.8 

51.8 

54.3 

56.8 

59.3 

61.8 

64.3 

66.8 

69.3 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

47.9 

50.9 

53.4 

55.9 

58.4 

60.9 

63.4 

65.9 

68.4 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

10.4 

13.6 

16.8 

20.0 

23.3 

26.5 

29.7 

32.9 

35.9 

38.9 

41.9 

44.9 

47.9 

50.9 

53.4 

55.9 

58.4 

60.9 

63.4 

65.9 

68.4 

70.0 

70.0 

49.8 

52.8 

55.3 

57.8 

60.3 

62.8 

65.3 

67.8 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

24.2 

27.2 

30.2 

33.2 

36.2 

39.2 

42.2 

45.2 

48.2 

51.2 

53.7 

56.2 

58.7 

61.2 

63.7 

66.2 

68.7 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

25.8 

28.8 

31.8 

34.8 

37.8 

40.8 

43.8 

46.8 

49.8 

52.8 

55.3 

57.8 

60.3 

62.8 

65.3 

67.8 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

FINAL REPORT  

19 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3.0% annual increase from 2013 baseline until 50% recycling rate achieved, thereafter progress at 2.5% per annum 

Member State 

1
3
1
0
2

4
1
0
2

5
1
0
2

6
1
0
2

7
1
0
2

8
1
0
2

9
1
0
2

0
2
0
2

1
2
0
2

2
2
0
2

3
2
0
2

4
2
0
2

5
2
0
2

6
2
0
2

7
2
0
2

8
2
0
2

9
2
0
2

0
3
0
2

1
3
0
2

2
3
0
2

3
3
0
2

4
3
0
2

5
3
0
2

Romania3 
Slovakia 

Slovenia 

Spain 

Sweden 

United Kingdom 

Notes:  

10.0 

13.0 

16.0 

19.0 

22.0 

25.0 

28.0 

31.0 

34.0 

37.0 

40.0 

43.0 

46.0 

49.0 

52.0 

54.5 

57.0 

59.5 

62.0 

64.5 

67.0 

69.5 

70.0 

10.8 

13.8 

16.8 

19.8 

22.8 

25.8 

28.8 

31.8 

34.8 

37.8 

40.8 

43.8 

46.8 

49.8 

52.8 

55.3 

57.8 

60.3 

62.8 

65.3 

67.8 

70.0 

70.0 

42.7 

45.7 

48.7 

51.7 

54.2 

56.7 

59.2 

61.7 

64.2 

66.7 

69.2 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

30.0 

33.0 

36.0 

39.0 

42.0 

45.0 

48.0 

51.0 

53.5 

56.0 

58.5 

61.0 

63.5 

66.0 

68.5 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

49.5 

52.5 

55.0 

57.5 

60.0 

62.5 

65.0 

67.5 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

43.5 

46.5 

49.5 

52.5 

55.0 

57.5 

60.0 

62.5 

65.0 

67.5 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

70.0 

1.  Baseline data obtained from Eurostat (2015) Municipal Waste [env_wasmun], Date Accessed: 23 June 2015, Downloaded from: 

http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasmun&lang=en 

2.  Bulgaria, Latvia, and Malta will have to increase preparation for reuse/recycling rates by more than 3% per annum in order to achieve the 50% target by 2020 

(using their chosen calculation method). As these countries are already obliged to meet this target it has been assumed that they will follow the Full 
Implementation trajectory until 2020 before commencing with the stated progression rates.  

3.  To account for the fact that Romania’s reported recycling rate does not include all household packaging and materials collected for recycling by the informal sector  

it has been assumed that the baseline recycling rate in 2013 is 10% (as opposed to the 2.55% reported to Eurostat). See main text for further details. 

20 

28/05/2015 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2.4.1 

Change in Final Management Destinations 

Achieving the targets set out in 

FINAL REPORT  

1 

 
  would mean that, relative to the Full Implementation scenario, the EU28 would have to 
increase recycling rates by close to 22%. The increased recycling rates are offset by a 
corresponding decrease in the amount of residual waste requiring treatment or disposal. 
Across the EU28 landfilling and incineration are both shown to decrease steadily until each 
Member State reaches 70% by 2035. The mass loss line represents losses from MBT 
processes, the use of which is also substantially reduced under this scenario. These effects 
occur because in some countries, investments in incineration and MBT are made in the full 
implementation scenario, so the higher target effectively forestalls some of the investment 
in incineration and MBT that would have otherwise been made in these countries. 

Figure 2-9: Final Management Destinations of Waste in Adjusted 70% MSW 
Recycling Scenario Relative to Full Implementation, EU28, 2011-2035 

2.4.2 

Financial Costs 

Under this scenario, the overall costs across the EU28 are lower than under Full 
Implementation. This is as a result of significantly reduced residual waste collection and 
treatment costs which outweigh the increased cost of recycling and biowaste treatment. As 
with previous results, it is important to understand the context of these changes – the Full 
Implementation scenario assumes that many countries have already had to invest 
significantly to upgrade collection services. 

As indicated on the graph below, the benefits are felt steeply from 2017, as initially all 
Member States increase their recycling performance at the same rate. As more and more 
countries reach 70% recycling the rate of progress slows until all Member States reach the 
final 70% MSW target in 2035. 

0 

28/05/2015 

-14%-12%-10%-8%-6%-4%-2%0%2%4%6%8%10%12%14%16%18%20%22%24%2011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Change in Final Management Destinations, %RecyclingIncinerationLandfillMass Loss 
 
Figure 2-10: Financial Costs of Adjusted 70% MSW Recycling Scenario Relative 
to Full Implementation, EU28, 2012-2035 

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

2.4.3 

Environmental Costs 

There are significant environmental benefits from increased recycling, primarily from 
avoided GHG emissions from recycling but also avoided GHG emissions from residual waste 
treatment and disposal (Figure 2-11).  The environmental benefits continue to accrue over 
time due to the fact that landfill causes ongoing methane emissions with damage costs 
which increase over time.  

FINAL REPORT  

1 

-€8,000-€6,000-€4,000-€2,000€0€2,000€4,000€6,000€8,0002011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Financial Costs, Million EUR 2015 Real TermsResidual Waste Collection CostsRecycling Collection CostsLandfill CostsMBT CostsIncineration CostsOrganic Treatment CostsWaste Prevention CostsNet Costs 
 
Figure 2-11: Environmental Costs of Adjusted 70% MSW Recycling Scenario 
Relative to Full Implementation, EU28, 2012-2035 

Note: Positive external costs denote a cost to society whilst negative costs represent a benefit. 

2.4.4 

Net Social Costs and Employment 

Under this scenario many Member States are assumed to reach 70% preparation for 
reuse/recycling before 2030. This means that all financial savings and environmental 
benefits are achieved earlier in time. The net position of this scenario is therefore very 
favourable.  Figure 2-12 below shows that by 2035 the net social benefit amounts to €6 
billion per year across the EU28 (in 2015 real term prices).  

2 

28/05/2015 

-€6,000-€5,000-€4,000-€3,000-€2,000-€1,000€0€1,000€2,0002011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Externalities, Million EUR 2015 Real TermsCollection & sorting - AQCollection & sorting - GHGsLandfill - AQ + OtherLandfill - GHGsIncineration - AQ + OtherIncineration - GHGsMBT etc - AQ + OtherMBT etc - GHGsOrganic Treatment - AQ + OtherOrganic Treatment - GHGsDry Recycling - AQ + OtherDry Recycling - GHGsWaste Prevention - AQ + OtherWaste Prevention - GHGsNet Externalities 
 
Figure 2-12: Net Social Costs of Adjusted 70% MSW Recycling Scenario 
Relative to Full Implementation, EU28, 2012-2035 

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

With a view of the net social costs across all Member States, it is evident that under this 
scenario all Member States, other than Malta, Poland and Romania, experience a net social 
benefit (Table 2-6). For the EU28 as a whole the NPV (2015-2035) shows a net benefit of 
€45.53 billion in 2015 real term prices. This is substantially higher than the scenarios above 
because of the higher recycling target and because the financial savings and environmental 
benefits are realised much earlier (meaning that they are not as heavily discounted).   

The estimated increase in direct employment is 117 thousand FTEs across the EU28 by 2035. 
This is higher than the rate achieved under the 65% recycling targets discussed above 
because a greater volume of material will be sent for recycling (which is more labour 
intensive than was disposal or incineration).   

Table 2-6: 65% Preparation for Reuse and Recycling Target vs Full 
Implementation – Net Social Costs and Benefits by Member State, Employment, 
and Greenhouse Gas Reduction 

Financial 
Costs 

External 
Costs 

Net Social 
Costs 

Employment 

Greenhouse Gas Reduction 

Member State 

NPV 2015-2035, € Billion 2015 Real 
Term Prices 

1,000 FTEs 
in 2030 

Austria 
Belgium 
Bulgaria 
Croatia 
Cyprus 

-0.66 
-0.37 
-0.01 
-0.13 
-0.14 

-0.51 
-0.52 
-0.12 
-0.25 
-0.08 

-1.17 
-0.89 
-0.13 
-0.37 
-0.22 

1.6 
1.2 
0.4 
2.6 
0.3 

Million 
Tonnes CO2 eq 
in 2030 
-0.60 
-0.22 
-0.30 
-0.51 
-0.19 

Million Tonnes 
CO2 eq, 2015-
2030 
-8.04 
0.26 
-1.68 
-2.39 
-1.30 

FINAL REPORT  

3 

-€7,000-€6,000-€5,000-€4,000-€3,000-€2,000-€1,000€0€1,0002011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035Costs, Million EUR 2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Member State 

Czech Republic 
Denmark 
Estonia 
Finland 
France 
Germany 
Greece 
Hungary 
Ireland 
Italy 
Latvia 
Lithuania 
Luxembourg 
Malta 
Netherlands 
Poland 
Portugal 
Romania 
Slovakia 
Slovenia 
Spain 
Sweden 
United Kingdom 
EU28 

Financial 
Costs 

External 
Costs 

Net Social 
Costs 

Employment 

Greenhouse Gas Reduction 

NPV 2015-2035, € Billion 2015 Real 
Term Prices 

1,000 FTEs 
in 2030 

-0.15 
-0.45 
-0.01 
-0.05 
-5.52 
-2.02 
0.21 
0.04 
-0.46 
-7.86 
-0.02 
0.10 
-0.04 
0.03 
-0.78 
1.50 
0.34 
0.84 
0.10 
0.03 
-0.95 
-0.29 
-0.67 
-17.39 

-0.44 
-0.13 
-0.06 
-0.09 
-7.89 
-0.98 
-0.45 
-0.77 
-0.38 
-6.09 
-0.03 
-0.16 
-0.03 
-0.02 
-0.69 
-0.75 
-0.59 
-0.62 
-0.26 
-0.12 
-0.83 
-0.29 
-5.02 
-28.14 

-0.59 
-0.58 
-0.07 
-0.14 
-13.41 
-3.00 
-0.24 
-0.73 
-0.83 
-13.95 
-0.04 
-0.06 
-0.07 
0.02 
-1.47 
0.75 
-0.25 
0.22 
-0.16 
-0.09 
-1.78 
-0.58 
-5.70 
-45.53 

1.6 
0.8 
0.3 
0.7 
24.5 
3.4 
1.9 
3.1 
1.5 
17.1 
0.3 
0.7 
0.0 
0.1 
2.2 
12.5 
3.7 
1.9 
0.8 
0.2 
6.0 
0.5 
27.6 
117.4 

Million 
Tonnes CO2 eq 
in 2030 
-0.75 
-0.05 
-0.13 
-0.09 
-7.46 
-0.99 
-0.96 
-1.25 
-0.84 
-6.73 
-0.09 
-0.31 
-0.02 
-0.04 
-0.60 
-1.72 
-1.15 
-1.39 
-0.48 
-0.13 
-1.74 
-0.14 
-5.93 
-34.79 

Million Tonnes 
CO2 eq, 2015-
2030 
-5.35 
3.10 
-1.86 
2.08 
-101.98 
19.28 
-8.15 
-13.94 
-9.74 
-80.61 
0.05 
-3.80 
-0.06 
-0.24 
-3.49 
-11.01 
-9.43 
-11.47 
-3.62 
-1.59 
-12.83 
2.00 
-68.08 
-333.91 

4 

28/05/2015 

 
 
 
 
3.0  Model Sensitivities 

Under this contract a ‘sensitivity test tool’ was integrated into the Municipal Waste Model to 
allow model users to assess how sensitive the model outputs are to key input assumptions. 
This section presents the details of three sensitivity tests that were conducted using this new 
tool.      

3.1  Key Parameters 

Eunomia agreed with the European Commission that the parameters in Table 3-1 would be 
used for conducting the sensitivity tests (these parameters now form the basis of the 
sensitivity test tool that is included in the Municipal Waste Model). This table shows realistic 
upper and lower bounds, or percentage variances, for each of the parameters. In each case 
the central, or baseline, value used in the modelling of the policy options is also shown. In 
the discussions below the baseline scenario essentially refers to the model results that are 
generated using the default assumptions that are saved in the Municipal Waste Model.       

Table 3-1: Parameters Included in Sensitivity Analysis with Upper and Lower 
Ranges 

Variable 

Baseline 
Value 

Type 

Lower  Upper 

Material Losses1: Bring - Bulk collection (all groups) 
Paper & Card 

Glass 

Metals 

Plastics 

15% 

10% 

10% 

30% 

Textiles 
20% 
Material Losses1 : Kerbside no PAYT - Bulk collection (groups 3 and 4) 
12% 
Paper & Card 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

8% 

8% 

20% 

Lower / Upper 

Glass 

Metals 

Plastics 

Textiles 
Material Losses1: Kerbside no PAYT - Materials segregated (group 5) 
Paper & Card 

15% 

4% 

Glass 

Metals 

Plastics 

3% 

3% 

7% 

Textiles 
5% 
Material Losses1: Kerbside with PAYT - Bulk collection (groups 3 and 4) 
15% 
Paper & Card 

Glass 

Metals 

Plastics 

10% 

10% 

25% 

Textiles 
15% 
Material Losses1: Kerbside with PAYT - Materials segregated (group 5) 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

10% 
5% 
7% 
25% 
10% 

5% 
5% 
6% 
15% 
10% 

2% 
1% 
1% 
3% 
2% 

6% 
6% 
7% 
18% 
12% 

20% 
15% 
13% 
45% 
30% 

15% 
13% 
10% 
35% 
20% 

7% 
5% 
5% 
15% 
8% 

18% 
16% 
12% 
42% 
24% 

FINAL REPORT  

5 

 
Variable 

Baseline 
Value 

Type 

Lower  Upper 

Paper & Card 

Glass 

Metals 

Plastics 

Textiles 

Material Revenues - Paper & Card 

Material Revenues - Textiles 

Material Revenues - Glass 

Material Revenues - Steel 

Material Revenues - Aluminium 

Material Revenues - Plastics 

Collection System Efficiencies (variance) 

Weighted Average Cost of Capital - Vehicles 

Weighted Average Cost of Capital - Infrastructure 
Energy Prices - Direct Revenue for Supplying 
Electricity to Grid (€ per kWh) 
Energy Prices - Heat price (€ per kWh) 

Labour Costs (Collection) 

Global warming potential of methane  

Landfill gas capture rates 

Monetised value placed on GHG emissions (variance) 

Marginal Electricity Grid mix - minimum % 
renewables2 
Waste Prevention Effects per Household - Food 
Waste Collection (kg/household/year) 
Waste Prevention Effects per Household - PAYT 
(kg/household/year) 

Notes:  

5% 

3% 

3% 

8% 

5% 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

Lower / Upper 

€ 94.64 

€ 295.74 

€ 23.66 

€ 165.61 

€ 887.21 

€ 118.29 

0% 

8% 

% variance 

% variance 

% variance 

% variance 

% variance 

% variance 

% variance 

Lower / Upper 

10% 

Lower / Upper 

 MS specific 

% variance 

 MS specific 

MS specific 

% variance 

% variance 

25 

Lower / Upper 

50% 
See 
schedule3 
No 
minimum 

Lower / Upper 

% variance 

Lower / Upper 

2% 
1% 
1% 
4% 
2% 
-40% 

-40% 

-25% 

-40% 

-40% 

-40% 

-15% 

3% 

4% 

-25% 

-25% 

-10% 

25 

20% 

-15% 

No 
minimum 

-10 

Lower / Upper 

-20 

Lower / Upper 

-40 

-60 

8% 
6% 
6% 
18% 
10% 
10% 

10% 

10% 

10% 

10% 

10% 

15% 

9% 

12% 

10% 

10% 

20% 

34 

70% 

15% 

50% 

-5 

-10 

1. Material losses relate to losses from collection through to reprocessing and is given as a percentage of the 
total amount of material collected for recycling. 

2. A value of 50% means that by 2030, it is assumed that all EU 28 countries have a marginal electricity grid mix 
of at least 50% renewable energy. 

3. Central assumptions on monetised values of GHG emissions vary each year as show in the table below: 

2011 -2025 

2026 

2027 

2028 

2029 

2030 

2031 

2032 

2033 

2034 

2035 

€ 32.0 

€ 32.6  € 33.2  € 33.8  € 34.4  € 35.0  € 39.4  € 43.8  € 48.2  € 52.6  € 57.0 

3.2  Approach to Analysing Sensitivities 

For the purpose of conducting the sensitivity tests, the scenario which examined the 70% 
preparation for reuse/recycling target in 2030 from the target review Impact Assessment 
was selected. In the Impact Assessment this option was identified as Option 3.1-High and for 

6 

28/05/2015 

 
 
 
the sake of consistency is referred to here by the same name.15 The analysis was conducted 
in the updated Municipal Waste Model and therefore the results, as described in Section 2.1, 
are not identical to those which appear in the Impact Assessment.  

The sensitivity analyses presented below consider the following three options: 

1)  A sensitivity assessment of the modelled Net Present Value (NPV)16 of the Full 

Implementation scenario; 

2)  A sensitivity assessment of the modelled NPV of Option 3.1-High; and 
3)  A further sensitivity assessment of the difference in NPV between Option 3.1-High 

and the Full Implementation scenario. 

The first two options highlight the potential variance in the overall costs or benefits of these 
scenarios caused by varying key parameters as shown in Table 3-1.  The last test will show 
whether, despite key parameters being flexed to upper / lower values, the relative benefit of 
moving from Full Implementation to 70% MSW preparation for reuse / recycling in 2030 is 
maintained, or whether a relative cost will be incurred. Depending on the changes that arise 
from flexing the input assumptions it may be necessary to draw different conclusions. The 
results of the sensitivity tests are presented below, with a brief explanation being provided 
for the key parameters. It will be seen from this discussion that even with varying the 
parameters between their likely extremes the overall conclusions of the original analysis do 
not change.  

3.3  Results of Sensitivity Tests 

When using the Municipal Waste Model’s baseline assumptions the NPV (2015 – 2030 in 
2015 real term prices) of the Full Implementation scenario is calculated to be €420 billion. 
This compares to an equivalent NPV of €404 billion for Option 3.1-High. Thus, relative to the 
Full Implementation scenario, Option 3.1-High results in a net social benefit to society of -
€16 billion (negative costs denote a benefit to society).17    

The sensitivity tests conducted as part of this work are intended to ascertain the degree to 
which these baseline cost calculations would change if the inputs to the model were flexed 
in the manner outlined in Table 3-1 above. Figure 3-1 to Figure 3-6 present the results of the 
sensitivity analysis for the three options listed above. The results are presented in both 
absolute (i.e. NPV in € billions) and relative terms (as a % variance from the baseline case). 

15 See European Commission (2014) Impact Assessment Accompanying the Document: Proposal for Reviewing 
the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm; alternatively, see Option 3.1.c in Eunomia 
Research & Consulting, Copenhagen Resource Institute, and Öko-Institut (2014) Impact Assessment on Options 
Reviewing Targets in the Waste Framework Directive, Landfill Directive and Packaging and Packaging Waste 
Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 
16 The net present value is the current value of a stream of future payments, in this case discounted at the 
social discount rate of 4%. 
17 The updated Municipal Waste Model was used for conducting these sensitivity tests and thus the NPV figures 
reported here do not match those presented in the impact assessment – see Section Error! Reference source 
not found. for more details. 

FINAL REPORT  

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These figures identify the 19 most critical assumptions which are arranged in descending 
order of priority.  

It can be seen from Figure 3-1 and Figure 3-2 that the five most important input assumptions 
which impact on the final NPV figure of the Full Implementation scenario are: 

1)  Labour costs associated with collection – reducing all of the Member State specific 
labour costs by 10% results in the calculated NPV falling from €420 billion to €410 
billion (i.e. a reduction of 2.52%). In contrast, increasing labour costs by 20% causes 
the NPV to rise to €441 billion (i.e. an increase of 5.04%). 

2)  Collection system efficiencies – the baseline input assumption assumes 0% gain in 
collection efficiencies. However, if one decreases or increases this by 15% in either 
directing the NPV of the Full Implementation scenario will range from a low of €407 
billion (-3.03%) to a high of €431 billion (2.65%). 

3)  Material losses – varying material losses as shown in Table 3-1 causes the calculated 
NPV of the Full Implementing scenario to vary between a low of €410 billion (-2.53%) 
and a high of €430 billion (2.34%).  

4)  Material revenue from paper and card – the assumed baseline revenue received for 
the sale of paper and card is €94.64 per tonne. If one decreases this by 40% the 
calculated NPV for the Full Implementation scenario falls to €416 billion (-0.91%). 
Alternatively, if it increases by 10% the NPV of this scenario will rise to €438 billion 
(3.64%). 

5)  Energy prices – reducing all of the Member State specific energy prices by -25% 
results in the calculated NPV falling to €417 billion (-0.78%). On the other hand, 
increasing prices by 10% would result in the NPV rising from €420 billion to €428 
billion (1.95%). 

Figure 3-3 and Figure 3-4 show the key model sensitivities for Option 3.1-High. It is evident 
that the five most sensitive input assumptions are identical to those identified above. 
However, the absolute and relative changes in the calculated NPV vary due to the fact that 
as Member States move towards 70% recycling the Model assumes that they have to adapt 
their collection systems, moving progressively towards pay as you throw type schemes (see 
Appendix A.3.0 for a description of how waste collections are assumed to change over time). 
The impact of the five assumptions which have the biggest influence on the calculated NPV 
figure for Option 3.1-High can be summarised as follows: 

1)  Labour costs associated with collection – reducing all of the Member State specific 
labour costs by 10% results in the calculated NPV falling from €404 billion to €393 
billion (i.e. a reduction of 2.64%). In contrast, increasing labour costs by 20% causes 
the NPV to rise to €425 billion (i.e. an increase of 5.28%). Per tonne of waste 
collected, the collection of recyclables is more labour intensive than collecting 
residual waste. Given that Option 3.1-High models a shift towards 70% recycling in 
2030 it is not surprising that the relative variance in the NPV figure is greater here 
than under the Full Implementation scenario which has a maximum recycling rate of 
50% being achieved in 2020. 

2)  Collection system efficiencies – the baseline input assumption assumes 0% gain in 
collection efficiencies. However, if one decreases or increases this by 15% in either 
directing the NPV of the Full Implementation scenario will range from a low of €391 
billion (-3.05%) to a high of €414 billion (2.61%). In relative terms, changes in the 

8 

28/05/2015 

 
assumed collection efficiencies has a similar impact under Option 3.1-High as under 
the Full Implementation scenario.    

3)  Material losses – varying material losses as shown in Table 3-1 causes the calculated 
NPV of the Full Implementing scenario to vary between a low of €393 billion (-2.69%) 
and a high of €414 billion (2.62%). The relative fluctuation in the NPV is greater for 
Option 3.1-High because much more material is being collected for recycling and thus 
material losses are greater (it is more expensive to collect recyclables that residual 
waste). 

4)  Material revenue from paper and card – the assumed baseline revenue received for 
the sale of paper and card is €94.64 per tonne. If one decreases this by 40% the 
calculated NPV for the Full Implementation scenario falls to €400 billion (-1.05%). 
Alternatively, if it increases by 10% the NPV of this scenario will rise to €421 billion 
(4.19%). Again, the relative variance in the NPV figure is greater than under the Full 
Implementation scenario because Option 3.1-High assumes much higher recycling 
rates and therefore one would expect higher revenues from the sale of dry 
recyclables (in this case paper and card). 

5)  Energy prices – reducing all of the Member State specific energy prices by -25% 
results in the calculated NPV falling to €400 billion (-0.73%). On the other hand, 
increasing prices by 10% would result in the NPV rising from €404 billion to €411 
billion (1.84%).  In this instance the relative change in the NPV resulting from flexing 
the input assumption on energy prices results in lower variance than under the Full 
Implementation scenario. This is because smaller volumes of residual waste are being 
sent to landfill and incineration under Option 3.1-High which means that less energy 
is being produced and sold to the grid.   

In summary, the results of separate sensitivity analyses on the Full Implementation and 
Option 3.1-High indicate that the total cost of waste management is most sensitive to 
variations in key operational costs and efficiencies, notably labour costs and collection 
system efficiencies, material losses (reflecting the differing amount of waste that would 
need collecting to meet a set final recycling rate), key revenue streams including the value of 
materials (especially of paper and card) and from the revenue gained for supplying 
electricity to the grid. In addition, the variation in the weighted average cost of capital 
(WACC) of both vehicles and infrastructure (due to high capital requirements in waste 
management) and the variation in marginal electricity grid mix (related to impacts from 
offset energy production) are in the top 10 most important assumptions for these two 
scenarios. 

FINAL REPORT  

9 

 
 
 
Figure 3-1: Variance in Social Cost of Waste Management in the EU28, under 
Full Implementation (NPV over 2015 – 2030 in 2015 Real Term Prices) 

Baseline value: 

NPV based on the 
Municipal Waste 
Model’s baseline 
assumptions (i.e. 
€420 billion) 

10 

28/05/2015 

409.60407.47409.58435.48428.39420.19413.51426.02425.56423.89423.20417.47418.77418.24421.27420.73419.78420.32420.19441.38431.34430.04416.37416.91428.41421.60418.74418.85419.27419.44420.56421.62420.94419.76419.84420.12420.14420.24405410415420425430435440445Labour Costs (Collection)Collection System Efficiencies (variance)Material Losses: AllMaterial Revenues - Paper & Card (EUR)Energy Prices - Direct Revenue for SupplyingElectricity to Grid (EUR per kWh)Marginal Electricity Grid mix - minimum % renewablesWeighted Average Cost of Capital - VehiclesMaterial Revenues - Plastics (EUR)Material Revenues - Steel (EUR)Material Revenues - Aluminium (EUR)Material Revenues - Textiles (EUR)Waste Prevention Effects per Household - Food WasteCollectionMonetised value placed on GHG emissions (variance)Weighted Average Cost of Capital - InfrastructureMaterial Revenues - Glass (EUR)Landfill gas capture ratesWaste Prevention Effects per Household - PAYTEnergy Prices - Heat price (EUR per kWh)Global warming potential of methaneNPV 2015-2030 (billion EUR, 2015 Real Term Prices)NPV with variable below baseline valueNPV with variable above baseline value 
 
 
 
Figure 3-2: Variance in Social Cost of Waste Management in the EU28, under 
Full Implementation (NPV over 2015 – 2030, % Change) 

Baseline value: 

NPV based on the 
Municipal Waste 
Model’s baseline 
assumptions (i.e. 
€420 billion) 

FINAL REPORT  

11 

-2.52%-3.03%-2.53%3.64%1.95%0.00%-1.59%1.39%1.28%0.88%0.72%-0.65%-0.34%-0.46%0.26%0.13%-0.10%0.03%0.00%5.04%2.65%2.34%-0.91%-0.78%1.96%0.33%-0.35%-0.32%-0.22%-0.18%0.09%0.34%0.18%-0.10%-0.08%-0.02%-0.01%0.01%-4%-3%-2%-1%0%1%2%3%4%5%6%Labour Costs (Collection)Collection System Efficiencies (variance)Material Losses: AllMaterial Revenues - Paper & Card (EUR)Energy Prices - Direct Revenue for SupplyingElectricity to Grid (EUR per kWh)Marginal Electricity Grid mix - minimum % renewablesWeighted Average Cost of Capital - VehiclesMaterial Revenues - Plastics (EUR)Material Revenues - Steel (EUR)Material Revenues - Aluminium (EUR)Material Revenues - Textiles (EUR)Waste Prevention Effects per Household - Food WasteCollectionMonetised value placed on GHG emissions (variance)Weighted Average Cost of Capital - InfrastructureMaterial Revenues - Glass (EUR)Landfill gas capture ratesWaste Prevention Effects per Household - PAYTEnergy Prices - Heat price (EUR per kWh)Global warming potential of methanePercentage Variance in NPV 2015-2030NPV with variable below baseline valueNPV with variable above baseline value 
 
 
 
  
 
 
Figure 3-3: Variance in Social Cost of Waste Management in the EU28, under 
Option 3.1-High (NPV over 2015 – 2030 in 2015 Real Term Prices)  

Baseline value: 

NPV based on the 
Municipal Waste 
Model’s baseline 
assumptions (i.e. 
€404 billion) 

12 

28/05/2015 

393.17391.52392.97420.78411.25410.80396.95409.71403.84399.58407.90407.72400.29401.19405.00403.22404.26403.95403.84425.17414.36414.43399.60400.87402.10405.29402.37411.15404.82402.82402.87404.37404.85403.38404.46403.56403.79403.75389394399404409414419424429Labour Costs (Collection)Collection System Efficiencies (variance)Material Losses: AllMaterial Revenues - Paper & Card (EUR)Energy Prices - Direct Revenue for SupplyingElectricity to Grid (EUR per kWh)Material Revenues - Plastics (EUR)Weighted Average Cost of Capital - VehiclesMaterial Revenues - Steel (EUR)Marginal Electricity Grid mix - minimum % renewablesWaste Prevention Effects per Household - PAYTMaterial Revenues - Aluminium (EUR)Material Revenues - Textiles (EUR)Waste Prevention Effects per Household - Food WasteCollectionWeighted Average Cost of Capital - InfrastructureMaterial Revenues - Glass (EUR)Monetised value placed on GHG emissions (variance)Landfill gas capture ratesEnergy Prices - Heat price (EUR per kWh)Global warming potential of methaneNPV 2015-2030 (billion EUR, 2015 Real Term Prices)NPV with variable below baseline valueNPV with variable above baseline value 
 
 
Figure 3-4: Variance in Social Cost of Waste Management in the EU28, under 
Option 3.1-High (NPV over 2015 – 2030, % Change)  

Baseline value: 

NPV based on the 
Municipal Waste 
Model’s baseline 
assumptions (i.e. 
€404 billion) 

Whereas the above discussion focused on the sensitivities of the two scenarios in isolation, 
Figure 3-5 and Figure 3-6 present the sensitivity results in relation to the net cost and benefit 
of moving from Full Implementation to Option 3.1-High. In the baseline case the difference 
between the NPV of the two scenarios is €16 billion – that is, there are net befits to be 
gained from moving from a position of Full Implementation (NPV €420 billion) to one which 
achieves 70% recycling in 2030 (NPV €404 billion). In the impact assessment, as well as the 
analysis presented in Section 2.0, all policy options are compared against the Full 

FINAL REPORT  

13 

-2.64%-3.05%-2.69%4.19%1.84%1.72%-1.71%1.45%0.00%-1.05%1.01%0.96%-0.88%-0.66%0.29%-0.15%0.10%0.03%0.00%5.28%2.61%2.62%-1.05%-0.73%-0.43%0.36%-0.36%1.81%0.24%-0.25%-0.24%0.13%0.25%-0.11%0.15%-0.07%-0.01%-0.02%-4%-3%-2%-1%0%1%2%3%4%5%6%Labour Costs (Collection)Collection System Efficiencies (variance)Material Losses: AllMaterial Revenues - Paper & Card (EUR)Energy Prices - Direct Revenue for SupplyingElectricity to Grid (EUR per kWh)Material Revenues - Plastics (EUR)Weighted Average Cost of Capital - VehiclesMaterial Revenues - Steel (EUR)Marginal Electricity Grid mix - minimum % renewablesWaste Prevention Effects per Household - PAYTMaterial Revenues - Aluminium (EUR)Material Revenues - Textiles (EUR)Waste Prevention Effects per Household - Food WasteCollectionWeighted Average Cost of Capital - InfrastructureMaterial Revenues - Glass (EUR)Monetised value placed on GHG emissions (variance)Landfill gas capture ratesEnergy Prices - Heat price (EUR per kWh)Global warming potential of methanePercentage Variance in NPV 2015-2030NPV with variable below baseline valueNPV with variable above baseline value 
 
 
Implementation scenario. As such, it is also important to understand how varying the value 
of key assumptions may affect the net difference between the two scenarios and therefore 
the overall benefit to be derived in making the transition to higher recycling rates.      

Figure 3-5: Variance in Social Cost of Waste Management in the EU28, Option 
3.1-Hiogh Compared to Full Implementation (NPV over 2015 – 2030 in 2015 Real 
Term Prices)  

Baseline value: 

NPV based on the 
Municipal Waste 
Model’s baseline 
assumptions the 
difference 
between Full 
Implementation 
and Option 3.1-
High = €16.3 
billion 

14 

28/05/2015 

-20.19-14.70-15.55-15.21-17.14-15.48-15.95-16.61-17.18-17.05-16.35-15.86-15.98-16.55-16.43-16.46-16.35-16.27-16.37-15.30-16.77-17.16-16.64-16.04-16.57-16.98-15.62-16.19-16.09-17.26-16.48-16.45-16.31-16.21-16.28-16.48-16.39-16.35-21-20-19-18-17-16-15Waste Prevention Effects per Household - PAYTMaterial Revenues - Paper & Card (EUR)Monetised value placed on GHG emissions (variance)Material Revenues - Plastics (EUR)Energy Prices - Direct Revenue for SupplyingElectricity to Grid (EUR per kWh)Material Revenues - Textiles (EUR)Collection System Efficiencies (variance)Material Losses: AllWaste Prevention Effects per Household - Food WasteCollectionWeighted Average Cost of Capital - InfrastructureMarginal Electricity Grid mix - minimum % renewablesMaterial Revenues - Steel (EUR)Material Revenues - Aluminium (EUR)Weighted Average Cost of Capital - VehiclesLabour Costs (Collection)Landfill gas capture ratesGlobal warming potential of methaneMaterial Revenues - Glass (EUR)Energy Prices - Heat price (EUR per kWh)NPV 2015-2030 (billion EUR, 2015 Real Term Prices)NPV with variable below baseline valueNPV with variable above baseline value 
 
 
Figure 3-6: Variance in Social Cost of Waste Management in the EU28, Option 
3.1-High Compared to Full Implementation (NPV over 2015 – 2030, % Change)  

Baseline value: 

NPV based on the 
Municipal Waste 
Model’s baseline 
assumptions 

From Figure 3-5 and Figure 3-6 it is evident that the five assumptions which result in the 
greatest variance between Full Implementation and 70% recycling and preparation for reuse 
in 2030 (i.e. Option 3.1-High) are: 

1)  Waste prevention effects resulting from introducing pay as you throw schemes 

(PAYT) – when comparing Full Implementation to Option 3.1-High it is evident that 
the results are most sensitive to the assumed changes in the amount of waste that is 

FINAL REPORT  

15 

23.49%-10.12%-4.90%-6.97%4.78%-5.35%-2.47%1.57%5.03%4.28%0.00%-3.05%-2.26%1.23%0.44%0.68%0.00%-0.53%0.08%-6.44%2.53%4.93%1.74%-1.91%1.34%3.84%-4.50%-0.99%-1.64%5.56%0.76%0.57%-0.26%-0.89%-0.45%0.78%0.21%-0.03%-15%-10%-5%0%5%10%15%20%25%30%Waste Prevention Effects per Household - PAYTMaterial Revenues - Paper & Card (EUR)Monetised value placed on GHG emissions (variance)Material Revenues - Plastics (EUR)Energy Prices - Direct Revenue for SupplyingElectricity to Grid (EUR per kWh)Material Revenues - Textiles (EUR)Collection System Efficiencies (variance)Material Losses: AllWaste Prevention Effects per Household - Food WasteCollectionWeighted Average Cost of Capital - InfrastructureMarginal Electricity Grid mix - minimum %renewablesMaterial Revenues - Steel (EUR)Material Revenues - Aluminium (EUR)Weighted Average Cost of Capital - VehiclesLabour Costs (Collection)Landfill gas capture ratesGlobal warming potential of methaneMaterial Revenues - Glass (EUR)Energy Prices - Heat price (EUR per kWh)Percentage Variance in NPV 2015-2030NPV with variable below baseline valueNPV with variable above baseline value 
 
 
prevented by shifting to PAYT collection schemes. When waste is prevented there are 
significant financial savings as the material does not have to be collected or treated. 
The model baseline assumes that when households shift to PAYT collection schemes 
their waste arisings will fall by 20kg per year. This impact could potentially vary by as 
much as 10kg to 60kg per household per year (these are the upper and lower bounds 
shown in Table 3-1). The collections module in the Municipal Waste Model assumes 
that in order for higher recycling rates to be achieved municipalities have to shift 
towards adopting PAYT schemes. This means that the waste prevention impact under 
Option 3.1-High, which sees the widespread implementation of PAYT, is substantially 
higher than under Full Implementation. As such, varying the input assumption on the 
likely waste prevention impact of introducing PAYT has a significant impact on the 
net difference between the two scenarios. If the waste prevention impact is assumed 
to be 10kg per household per year the net difference between the two scenarios will 
rise slightly to -€15 billion (-6.44%). If the waste prevention impact is assumed to 
reach an upper limit of 60kg per household per year then the net difference falls 
markedly to -€20 billion (23.49%).   

2)  Material revenue from paper and card – the assumed baseline revenue received for 
the sale of paper and card is €94.64 per tonne. If one decreases this by 40% the 
difference in the NPV of the two scenarios rises from -€16 billion to -€15 billion (-
10.12%). Alternatively, if it increases by 10% the net position of the two scenarios will 
decrease to -€17 billion (2.53%). As noted above, given the difference in the recycling 
rates of the two scenarios it would be expected that material revenues play an 
import role (being higher under Option 3.1-High compared to Full Implementation). 
3)  Monetised value placed on greenhouse gas (GHG) emissions – given the additional 
GHG savings that are made under Option 3.1-High vs Full Implementation (see Table 
2-2) one would expect the assumed cost of GHG emissions to be a key driver in 
determining the net benefits. If the value of GHGs is varied by 15% in either direction 
the net position of the two scenarios will change from a high of -€15 billion (-4.90%) 
to a low of -€17 billion (4.93%). This demonstrates that this is an important 
assumption when considering the net positon of these two scenarios.      

4)  Material revenues plastics – as with material revenues from paper and card varying 
the baseline value for plastics has a noticeable impact on the final results. If the 
baseline value of €118.29 per tonne for plastics is reduced by 40% the comparative 
NPV figure rises to -€15 billion (-6.97%), whereas if the price of plastics is assumed to 
rise by 10% the difference in NPV figures falls to -€17 billion (1.74%).      

5)  Energy prices – reducing all of the Member State specific energy prices by -25% 

results in the net difference rising slightly by €0.3 billion (-1.94%). On the other hand, 
increasing prices by 10% would result in the difference decreasing by €1 billion to -
€17 billion (4.78%). As noted previously, this difference arises because Option 3.1-
High sees smaller amounts of electricity being generated through landfill gas and 
Energy from Waste. 

When one considers these changes in light of the absolute figures discussed above it is clear 
that they represent very small differences in the costs. For example, altering the assumed 
waste prevention impact generated by transitioning to PAYT will either cause the net 
difference between Option 3.1-High and Full Implementation to rise by €1 billion of fall by €4 
billion. If one compares this to the absolute NPV of €404 billion for Option 3.1-High this 
represents a shift of less than 1% in either direction. Thus, it is clear that from the sensitivity 

16 

28/05/2015 

 
tests conducted here that, although the model is clearly more sensitive to changes in some 
input assumptions than to others, the overall narrative and conclusions do not change 
significantly. It is therefore safe to assume that although the numbers may vary slightly if 
different input assumptions are used the overall conclusion that is being drawn will not 
change. 

The discussion above has only looked at the impact of varying input parameters 
independently rather than simultaneously. It is important to note, however, that even if a 
worst case scenario is taken –that is, all parameters are assumed to be at the lower / upper 
limits – the net benefit does not change to a net cost.  

FINAL REPORT  

17 

 
       
 
  
 
 
 
4.0  Modelling C&D Waste Flows 

The Terms of Reference (ToR) of this project required that a construction & demolition 
(C&D) waste model be developed with three scenarios included. This section introduces the 
C&D model by introducing the following: 

1)  Section 4.1 details the structure of the model that was developed in accordance with 

the Specifications set out in the contract; and 

2)  Sections 4.2 and 4.3 present the EU28 results for the Full Implementation and More 

Ambitious scenarios that have been generated by the model. 

4.1  Overview of C&D Model 

The C&D Waste Model allows for development of scenarios on the management and 
treatment of C&D waste in each of the 28 Member States. The model is much simpler than 
the model for MSW, and can be used to quantify the impact of different scenarios in respect 
of financial impacts, impacts on the environment, job creation, and greenhouse gas 
emissions. It thereby allows for the overall costs and benefits of different scenarios to be 
calculated out to 2035. As alluded to above, these impacts can be quantified for individual 
Member States or for the EU28 as a whole. It is important to note that the quality of the 
data is far lower than for the municipal waste model, and the underlying assumptions are 
less well grounded in evidence because there is a dearth of studies related to C&D waste 
costs and benefits in the EU. This is another reason for the relative simplicity of the model. 

The overall structure of the model is shown graphically in Figure 4-1. A brief overview of 
each component of the model is provided in the sub-sections below. 

4.1.1 

Data Inputs and Assumptions 

There is very limited data available for C&D waste in Europe, and the quality of available 
data is relatively poor. One report suggests that the quantity of C&D waste per capita 
demonstrates considerable variation across Europe, much greater than would be expected 
even accounting for variations in economic conditions.18 The same study of C&D waste, 
which was published by the Commission in 2011, stated that these variations are mainly 
caused by “unequal levels of control and reporting of C&D waste in MS [Member States], as 
well as differences in definitions and reporting mechanisms”.19 Furthermore, many countries 
do not report, or appear to have no data for, C&D waste compositions, and up-to-date 
collection and treatment costs for C&D waste are not available from the literature.  

18 Bio Intelligence Service, Arcadis and IEEP (2011) Service Contract on Management of Construction and 
Demolition Waste – SR1, Report for the European Commission, February 2011, 
http://ec.europa.eu/environment/waste/pdf/2011_CDW_Report.pdf 
19 Ibid. 

18 

28/05/2015 

 
 
                                                   
 
Figure 4-1: Overview of the Construction and Demolition Waste Model 

FINAL REPORT  

19 

 
 
Wherever possible, input data for the model was sourced from publicly available reports and 
databases (see Appendix A.1.0 for full details of all input data and assumptions). These data 
were supplemented with professional expert judgements where necessary to fill in data 
gaps. Building up a more accurate picture of C&D waste arisings and associated costs would 
require extensive primary research which was beyond the scope of this study (a separate 
study has been let by DG Environment intending to fill some of these gaps). Given the 
increasing attention that is being placed on C&D waste, it is anticipated that the quality and 
quantity of data will begin to improve over the coming years and the model has been built 
with this in mind by allowing the user the option to modify all input assumptions should they 
wish to do so as better information becomes available. 

4.1.2 

Modelled Scenarios 

The model allows for developing four distinct scenarios, the first two of which can be used as 
the ‘baseline’ or ‘comparison’ scenario when comparing C&D policy options (the model user 
has the option to modify all scenarios if required). The four scenarios include the following: 

1)  Business as usual – Under this scenario it is assumed that recycling and backfilling 
are held constant at 2012 rates (the latest year for which data was available at the 
time the model was developed); 

2)  Full implementation – This scenario assumes that Member States meet the Waste 

Framework Directive target of 70% recycling and backfilling by 2020; 

3)  More ambitious target – This is similar to the full implementation scenario, however, 

this scenario does not allow Member States to use backfilling to meet the 70% 
recycling target; and 

4)  User defined scenario – this has been left free for the user to set up according to 
their own specification. Under this scenario the user has the option to modify the 
future projections for recycling and backfilling rates and can choose whether or not 
backfilling is included in the recycling rate calculation. 

4.1.3  Waste Flow Projections 

All calculations in the model are performed for the ‘baseline’ and ‘comparison’ scenario 
simultaneously. The results of these calculations are then compared to estimate the relative 
change in waste flows, financial costs, and environmental impacts from moving from one 
scenario to another. In this way the model calculates the relative costs and benefits 
associated moving from one policy scenario – for example, business as usual – to another, 
usually more ambitious scenario, such as a 70% material recovery target.    

The first stage of calculations constructs a forward projection to 2035 for C&D waste arisings 
and overall treatment tonnages. The rate of growth of C&D waste used in this calculation is 
linked to GDP growth for each country through the application of a specific factor (there is 
an element of decoupling - see Appendix A.1.0 for a more detailed discussion). The 
quantities of waste going to recycling, backfill, incineration, and landfill are then estimated 
based on the recycling and backfilling trajectories defined for each scenario. 

4.1.4 

Assessment of Impacts 

The C&D Model quantifies the impacts of a change in scenarios and provides outputs in a 
simple tabular and graphic form. Outputs are generally presented in terms of the relative 

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differences between scenarios, rather than as absolute values. The following outputs are 
provided by the model: 

1)  Waste Flows and Treatment Rates – the model calculates the proportion of C&D 
waste going to each treatment type for each scenario and associated tonnages; 

2)  Environmental Benefits – Three types of impacts are analysed:  

a.  the climate change impacts (in terms of tonnes of CO2 equivalent); 
b.  the monetised environmental costs and benefits of both the climate change 
impacts, together with those impacts associated with other emissions to air 
such as NOx, SOx, and PM. Pollutant impacts are given a monetary value, such 
that the outcome can be considered in € (the monetary value of these 
impacts are based on those used in the Municipal Waste Model); and 20 

c.  Avoided disamenities, both from the reduced extraction of primary 

aggregates/soils and minerals enabled by recycling (i.e. the disbenefits 
associated with living in the vicinity of a quarry) and from 
landfilling/backfilling (i.e. the disbenefits associated with living in the vicinity 
of a landfill). 

3)  Financial Benefits – the model assesses the total change in C&D waste collection and 
treatment costs in the comparison scenario relative to the chosen baseline scenario; 

4)  Employment Impacts – the change in the number of direct Full Time Equivalents 
(FTEs) associated with the collection and treatment of C&D waste is estimated;  
5)  Resource Efficiency Indicators – the following resource efficiency indicators are 

included: 

a.  Recycling, backfill and landfill rates; 
b.  The quantity of C&D waste generated per inhabitant; and 
c.  Greenhouse gas (GHG) savings relative to hypothetical maximum.21 
6)  Distance to Targets – the performance under the ‘comparison’ scenario relative to 
the European targets for C&D waste. The model assesses whether or not these 
targets are met and the distance to these targets for each year. 

4.2  Full Implementation Scenario 

This section presents summarised results from the C&D model for the EU28 (specific 
Member State reports are provided in Appendix A.2.0). These results provide an overview of 
the waste management performance of the Full Implementation scenario (70% recycling and 
backfilling by 2020) compared against the Business as Usual scenario (no change to recycling 
and backfilling rates). 

20 See Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment and European Environment Agency, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
21 The GHG savings analysed for the distance to targets relate to avoided emissions due to material recycling. 
The emissions avoided in the baseline and comparison scenarios are compared against the hypothetical 
emissions avoided if 100% of collected C&D waste was recycled. 

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4.2.1 

Change in Final Management Destinations 

As detailed in Figure 4-2, moving from the Business as Usual scenario to the Full 
Implementation scenario implies a 0.9% increase in recycling rates, and a 1.1% increase in 
backfilling rates, across the EU28. This increase is offset by a 2.0% reduction in landfill and a 
minor decrease (0.05%) in incineration of C&D waste. These shifts are minimal as the 
majority of Member States are already reporting that they have met the Waste Framework 
Directive target. 

Figure 4-2: Full Implementation vs Business as Usual – Change in Final 
Management (EU28) 

Figure 4-3 presents the difference in final management destinations between the Full 
Implementation and Business as Usual scenarios in 2020 for all Member States. It is 
important to note that only nine Member States (Bulgaria, Croatia, Cyprus, Finland, France, 
Greece, Malta, Romania and Slovakia) had combined recycling and backfilling rates below 
70% in 2012, and therefore, as shown in Figure 4-3, these are the only Member States for 
which a change in recycling and backfilling rates is required to meet the 70% material 
recovery target under the Full Implementation scenario. The fact that the majority of 
Member States show no change in final management destinations explains why, even 
though substantial shifts in final destinations are modelled for some Member States, the 
overall change in recycling and backfilling rates across the EU28 is relatively low. 

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Figure 4-3: Full Implementation vs Business as Usual – Change in Final 
Management by 2020 

4.2.2  Employment Impacts 

Moving from Business as Usual to Full Implementation may lead to an increase in 
employment (Figure 4-4). The estimated increase in direct employment is over 1.3 thousand 
FTEs (Full Time Equivalents) across the EU28 by 2020. This figure is low because only a 
relatively small change has to occur before Bulgaria, Croatia, Cyprus, Finland, France, 
Greece, Malta, Romania and Slovakia can meet the 70% recycling and backfilling target by 
2020.  All other countries are already doing so. 

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Figure 4-4: Full Implementation vs Business as Usual – Change in Employment 
by 2030 (Full Time Equivalent) 

4.2.3  Costs and Benefits    

4.2.3.1 

Financial Costs 

A comparison of the Full Implementation scenario against Business as Usual indicates that 
there are savings to be achieved if Member States meet the 70% material recovery target by 
2020. The overall financial savings achieved are shown in Figure 4-5. From this it is evident 
that estimated savings of over €23 million may be achieved by 2020. Most of the savings are 
achieved by increased diversion of waste from landfill to recycling: for glass, metals, soil and 
mineral waste the unit cost of recycling, net of revenues generated, is typically lower than 
the unit cost of landfill.  

For most materials, the unit cost of recycling is lower than the landfill unit cost mainly 
because collection costs for the separate collection of recyclate, once revenues are taken 
into account, are lower than collection costs for mixed waste collections (mixed waste 
collections are the primary collection method for waste that is sent to landfill). The fact that 
landfill gate fees do not apply to recycled material also contributes towards lower recycling 
unit costs.  

For other materials (wood and plastics), landfilling is less expensive than recycling. However, 
overall, for the range of materials considered, the increased level of recycling proves more 
cost effective than continuing landfilling in the EU28. 

4.2.3.2 

Environmental Costs 

There are clear environmental benefits to be gained from Full Implementation (Figure 4-5). 
Most of the benefits are due to the increased diversion of waste from landfill to recycling. A 

24 

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small environmental cost is observed for the diversion of wood from incineration to 
recycling. This is because the emissions avoided through energy generation in incinerator 
plants outweigh the environmental benefits of recycling.  

The majority of these benefits are realised prior to 2020 when the 70% material recovery 
target has to be met; however, the benefits continue to accrue steadily over time once the 
70% material recovery target is achieved. This is because of the way that emissions from 
landfill are accounted for and the fact the damage costs for greenhouse gases are assumed 
to increase over time. Waste landfilled in one year will continue to emit methane for a 
number of years afterwards. Thus, avoided landfilling under the Full Implementation 
scenario results in ongoing benefits beyond 2020. 

4.2.4  Net Costs and Benefits 

As noted above, there are both environmental and financial cost and benefits associated 
with moving from the Business as Usual to a situation where Member States are recycling or 
backfilling 70% of all C&D waste in 2020 (i.e. the Full Implementation scenario). The overall 
picture shows that the annual net benefits will increase steadily until 2020 to approximately 
€103 million, and will continue to increase at a slower rate to reach about €128 million in 
2030 and about €159 million per year by 2035. 

Figure 4-5: Full Implementation vs Business as Usual – Net Costs and Benefits 
(EU28)       

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

4.2.4.1  Net Present Value 

Figure 4-6 provides an indication of the NPV, in 2015 real terms, of the financial and 
environmental costs for each Member State (covering the period 2015 – 2035). In line with 

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the European Commission’s approach to impact assessments, a discount rate of 4% per 
annum was applied for each country. 

This figure demonstrates that approximately 82% of the net savings in the EU28 achieved 
over the period 2015 to 2035 would be in two countries,  France (14%) and Finland (68%). 
These countries are distinctive in that, while they generate the 2nd (France) and 7th (Finland) 
largest quantity of waste of any Member State (only Germany produces more than France), 
their recycling rates are relatively low compared to other countries that produce a large 
quantity of C&D waste. The average recycling rate (as reported by Eurostat) for the 10 
Member States which generate the most C&D waste was 77% in 2012.22,23 In comparison, 
the reported recycling rates for France and Finland were 59% and 12%, respectively. This 
means that for these two countries there is a significant difference in the final treatment 
destinations between the Business as Usual and Full Implementation scenarios, so there is a 
much more substantial shift to backfill and recycling than in other Member States which are 
also producing large quantities of C&D waste. This combination of high quantities of waste 
and a large change in treatment destinations results in a large difference in financial and 
environmental costs between the two modelled scenarios for France and Finland. 

Figure 4-6: Full Implementation vs Business as Usual – Net Costs and Benefits 
by Member State (NPV 2015-2035, 2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

22 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
23 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

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4.3  More Ambitious Scenario 

These results provide an overview of the waste management performance of the More 
Ambitious scenario which excludes backfilling from the target which is currently specified 
(i.e., this implies 70% recycling by 2020) compared against the Business as Usual scenario 
(i.e. no change to recycling and backfilling rates). 

4.3.1 

Change in Final Management Destinations 

As detailed in Figure 4-7 below, moving from the Business as Usual scenario to the More 
Ambitious scenario implies a 4.0% increase in recycling rates. This increase is offset by a 
1.1% reduction in backfilling, a 2.8% reduction in landfilling and a minor decrease (0.05%) in 
incineration of C&D waste. 

Figure 4-8 presents the difference in final management destinations between the More 
Ambitious and Business as Usual scenarios in 2020 for all Member States. It is important to 
note that only thirteen Member States (Bulgaria, Croatia, Cyprus, Czech Republic, Finland, 
France, Greece, Hungary, Malta, Poland, Romania, Slovakia and Spain) had recycling rates 
below 70% in 2012, and therefore, these are the only Member States for which a change in 
recycling rates is required to meet the 70% recycling target specified by the More Ambitious 
scenario. The fact that more than half of Member States show no change in final 
management destinations explains why, even though substantial shifts in recycling rates are 
modelled for some Member States, the overall change in recycling rates across the EU28 is 
relatively low. The impacts are also correspondingly small. 

Figure 4-7: More Ambitious vs Business as Usual – Change in Final 
Management (EU28) 

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Figure 4-8: More Ambitious vs Business as Usual – Change in Final 
Management by 2020 

4.3.2  Employment Impacts 

Moving from Business as Usual to the More Ambitious scenario leads to an estimated 
increase in direct employment by 2020 of 2.3 thousand FTEs (Full Time Equivalents), spread 
across those Member States who are not already recycling 70% (or more) of their C&D waste 
(Figure 4-9). 

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Figure 4-9: More Ambitious vs Business as Usual – Change in Employment by 
2030 (Full Time Equivalent) 

4.3.3  Costs and Benefits    

4.3.3.1 

Financial Costs 

A comparison of the More Ambitious scenario against Business as Usual indicates that there 
are savings to be achieved if Member States meet the 70% recycling target by 2020. The 
overall financial savings achieved are shown in Figure 4-10. From this it is evident that 
estimated savings of over €93 million may be achieved by 2020. 

4.3.3.2  As for the Full Implementation scenario (Section 4.2.3.1), most of 
these savings are achieved by increased diversion of waste from 
landfill to recycling. The diversion of waste from backfilling to 
recycling also leads to smaller but still significant savings; these are 
mainly achieved due to the lower collection costs for the separate 
collection of recyclate compared to mixed waste collections. A small 
saving is also achieved due to the avoided backfill preparation costs 
when recycling material rather than backfilling.Environmental Costs 

There are clear environmental benefits to be gained from the More Ambitious scenario 
(Figure 4-10). These benefits are mainly achieved through the increased diversion of waste 
from landfill to recycling, but are also due to the reduction in backfilling. The reduction in 
environmental costs resulting from a switch from backfilling to recycling are mainly due to 
the avoided disamenity from backfilling, that is, the disbenefits associated with living in the 
vicinity of a landfill/backfill site. 

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The majority of these benefits are realised prior to 2020 when the 70% recycling target has 
to be met, though the benefits continue to accrue steadily over time once the 70% recycling 
target is achieved (see Section 4.2.3.2 for a fuller discussion of this point). 

4.3.4  Net Costs and Benefits    

As noted above, there are both environmental and financial cost and benefits associated 
with moving from the Business as Usual to a situation where Member States are recycling 
70% of all C&D waste in 2020 (i.e. the More Ambitious scenario). The overall picture shows 
that the net benefits will increase steadily until 2020 to approximately €285 million, and will 
continue to accrue at a slower rate to reach about €356 million in 2030 and about €425 
million per year by 2035. 

Figure 4-10: More Ambitious vs Business as Usual – Net Costs and Benefits 
(EU28)   

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

4.3.4.1  Net Present Value 

Figure 4-11 provides an indication of the NPV, in 2015 real term prices, of the financial and 
environmental costs for each Member State (covering the period 2015 – 2035). In line with 
the European Commission’s approach to impact assessments, a discount rate of 4% per 
annum was applied for each country. 

A large proportion (85%) of the net savings in the EU28 achieved over the period 2015 to 
2035 are generated in France (52%) and Finland (32%). The reasons for this are outlined in 
the discussion for the Full Implementation scenario in Section 4.2.4.1. 

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Figure 4-11: More Ambitious vs Business as Usual – Net Costs and Benefits by 
Member State (NPV 2015-2035, 2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings. 

It is important to note that the model is based on C&D waste arisings and recycling rates 
reported to Eurostat, and the quality of these data are often questionable. As with any 
model, the quality of the outputs are only as good as the data inputs and underlying 
assumptions and these need to be born in mind when interpreting the results presented 
here. For further details on the limitations of the model please refer to Appendix A.1.0. 

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5.0  Member State Summary Reports 

In order to facilitate the easy dissemination of the results, and to allow for better 
understanding of how the model outputs are derived, Member State summary reports have 
been prepared based on the outputs of the Municipal Waste Model and the C&D model. 
These summary reports systematically present the results from the two models to show how 
the final costs and benefits are derived. These reports should, therefore, provide a good 
basis for understanding the basic outputs of the two models and how the results are built up 
to allow for the testing of different policy scenarios.   

The summary country reports relating the Municipal Waste Model are presented in 
Appendix A.3.0, whilst the C&D summary reports can be found in Appendix A.2.0. Please 
refer to these appendices for further details. 

Under Eunomia’s existing contract with the Commission the Municipal Waste Model has 
been updated in a number of ways. The key technical changes are summarised in Section 
2.1. It is important to note that the updated model has been used to produce the results 
which are presented in the country summary reports.  

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6.0  Modelling Imports and Exports of 
Municipal Solid Waste in Europe 

The Terms of Reference for this study required that Eunomia: 

“… assess the feasibility of modelling imports and exports of municipal waste. If it is 
found to be feasible after a discussion with the Commission and the EEA, the contractor 
shall develop a specific module on imports and exports of waste capturing the main 
possible impacts … of imports and exports of municipal waste. If not, he shall propose a 
set of precise actions to improve data quality on imports/exports of municipal waste 
notably in the light of the draft Commission proposals for the target review (notably 
the establishment of National registries)”. 

The first task was to review the available data in order to make a recommendation about 
whether imports and exports of MSW can, given the state of the data, be included within the 
European Reference Model on Municipal Waste Management. Section 6.1 reviews the 
available data at each tier of the waste hierarchy, before outlining our recommended 
approach for modelling imports / exports in Section 6.2. Section 6.3 concludes by providing 
an overview of how reporting on cross-border municipal waste flows could be improved in 
Europe, for example, in light of the establishment of national registries to track the cross-
border movement of municipal waste.     

6.1  Reviewing the Available Data 

6.1.1 

Member State Reporting Requirements 

This section outlines the legislation and policies which require Member States to report on 
transboundary shipments of waste. Where Member States are obliged to report on waste 
movements, one would expect, or at least hope, that data are available, and that they are 
accurate. Where there are no, or limited, reporting obligations, on the other hand, it can be 
very challenging to obtain reliable information on waste movements between countries.   

In 2012, the EEA summarised the regulations regarding the shipment of wastes into and out 
of European Member States.24 In essence, these movements are governed by the Waste 
Shipment Regulations of 200625, which implements both the Basel Convention and the OECD 
Council Decision C (2001)107/Final. 

Under these regulations waste can broadly be classified into ‘green list wastes’ and 
‘notifiable wastes’. The former are subject to less stringent controls and include materials 
listed in Annex III and IIIA, and which are not prohibited under Article 36 (these Annexes 

24 European Topic Centre on Sustainable Consumption and Production (2012) Transboundary Shipments of 
Waste in the European Union: Reflections on Data, Environmental Impacts and Drivers, Report for European 
Environment Agency, November 2012, http://scp.eionet.europa.eu/publications/wp2012_2 
25 Commission Regulation (EC) No 1013/2006 of the European Parliament and of the Council of 14th June 2006 
on Shipments of Waste, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:02006R1013-20130410 

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have subsequently been revised in Commission Regulation (EC) No. 308/2009). Green list 
wastes include all common dry recyclables, and these can be exported for recycling without 
notifying the competent authority (this was approved after consultation with numerous 
countries and published as Commission Regulation (EC) No. 1418/2007).26 Notifiable wastes 
are defined in Article 3 of the Waste Shipment Regulations and require that the person 
intending to ship these wastes provides the relevant competent authority with a notification 
and movement document for the waste. An overview of the requirements for permissible 
transfrontier shipments of waste are summarised in Table 6-1. Of course, for some wastes, 
where end-of-waste criteria exist, reporting on movements is not required since the material 
is no longer considered to be waste. For some materials (e.g. steel scrap), end of waste 
status is achieved before the reprocessing stage so that exports for reprocessing may occur 
for material which is no longer waste. 

It is widely acknowledged that the data being generated from the reporting of transfrontier 
shipments of wastes have a number of limitations including, for example, that historically 
waste movements were often reported using the ‘Y-codes’ established by the Basel 
Convention, and not the European Waste Catalogue (EWC) codes which provide a more 
accurate breakdown of waste streams by material and source (this has changed more 
recently and the vast majority of Member States now use EWC codes for their reporting).27 
In addition, the fact that green list wastes can be shipped without notifying the competent 
authority means that information on waste movements higher up the waste hierarchy is 
typically very poor. We examine below the quality of the available data at each tier of the 
waste hierarchy and what the prospects would be for including these flows in the municipal 
waste model.       

26 Commission Regulation (EC) No. 1418/2007, Concerning the Export for Recovery of Certain Waste Listed in 
Annex III or IIIA to Regulation (EC) No 1013/2006 of the European Parliament and of the Council to Certain 
Countries to which the OECD Decision on the Control of Transboundary Movements of Wastes does not Apply, 
http://trade.ec.europa.eu/doclib/docs/2007/december/tradoc_136966.pdf   
27 See for example: European Topic Centre on Sustainable Consumption and Production (2012) Transboundary 
Shipments of Waste in the European Union: Reflections on Data, Environmental Impacts and Drivers, Report for 
European Environment Agency, November 2012, http://scp.eionet.europa.eu/publications/wp2012_2 

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      Table 6-1: Overview of Permissible Transfrontier Waste Shipments under the Waste Shipment Regulations (WSR) 

Transboundary shipment 
within the EU 

Import into Bulgaria, 
Latvia, Poland, Romania, 
Slovakia 

Import into the EU 

Waste destined for recovery and 
listed in Annexes III ( ‘green’-list ), III 
A and IIIB 

No notification (*) 

Notification requirement 
case-specific subject to 
applicable transitional 
period (Art. 63, WSR) 

No notification (*) 

Export from the EU to 
countries to which the 
OECD decision applies 

Export out of the EU to 
countries to which the 
OECD decision does not 
apply 

Notification required (Art. 
38, WSR), except for 
waste listed in Annex III 
and IIIA (if no subsequent 
recovery takes place in a 
non-OECD country) 

Annex III & IIIA: 
Procedure laid down in 
Regulation 1418/2007, 
otherwise notification; 
Annex IIIB: Notification 
required  (Art.37(5), WSR) 

Transit through the EU 

No notification (*) 

Uncontaminated, non-hazardous 
waste listed in Annex V (List B of 
Part 1 and Part 2 — only wastes 
without accompanying asterisk) 

‘Amber’ -listed waste for recovery 
(Annexes IV and IVA); wastes not 
classified under one single entry in 
either Annex III, IIIB, IV or IVA; 
mixtures of wastes not classified 
under one single entry in either 
Annex III, IIIB, IV or IVA unless listed 
in Annex IIIA 

Hazardous waste for recovery 
subject to export prohibition 
according to the Basel Convention 
(Annex V) 

Notification required, 
unless the waste is also 
listed in the 'green'- list of 
Annex III (Title II, Art. 
3(1)(b)(iii), WSR) 

Notification required, 
unless no transitional 
period is applicable for 
the case of waste listed in 
Annex III 

When not prohibited, (a), 
notification required (Arts 
43–46, WSR), unless 
waste listed in Annex III 

Notification required 
unless waste listed in 
Annex III 

Notification required (Art. 
37(5), WSR) 

Notification required 
unless waste listed in 
Annex III 

Notification required 
(Title II, Art. 4, WSR) 

Notification required 
(Title II, Art. 4 WSR) 

When not prohibited, (a), 
notification required (Arts 
43–46, WSR) 

Notification required (Art. 
38, WSR) 

Prohibited (Art. 36, WSR) 

Notification required (Art. 
48, WSR) 

Notification required 
(Title II, Art. 4 WSR) 

Notification required 
(Title II, Art. 4 WSR) 

When not prohibited, (a) 
notification required (Arts 
43–46, WSR) 

Notification required (Art. 
38, WSR) 

Prohibited (Art. 36, WSR) 

Notification required (Art. 
48, WSR) 

Waste for disposal 

Notification required 
(Title II, Art. 4, WSR) 

Notification required 
(Title II, Art. 4, WSR) 

When not prohibited, (b) 
notification required (Arts 
41–42, WSR) 

Prohibited except to EFTA 
countries for which 
notification is required 
(Arts 34–35, WSR) 

Prohibited (Art. 34, WSR) 

Notification required (Art. 
47, WSR) 

(*) The requirements of Article 18 of the WSR should be observed. 
(a) The prohibition does not cover countries to which the OECD decision applies, parties to the Basel Convention or countries  with which EU has a bilateral agreement. 
(b) The prohibition does not cover parties to the Basel Convention or countries with which EU has a bilateral agreement. 
Original Source: EC, 2006a and CRI, 2011 based on input from Joachim Wuttke, the German Federal Environment Agency (UBA) and  George Kiayias, the European Commission. 

Source: European Topic Centre on Sustainable Consumption and Production (2012) Transboundary Shipments of Waste in the European Union: Reflections on Data, 
Environmental Impacts and Drivers, Report for European Environment Agency, November 2012, http://scp.eionet.europa.eu/publications/wp2012_2 

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6.1.2 

Preparation for Reuse and Recycling 

As noted above, wastes considered low risk to the environment fall within the defined 'green 
list' where there are lower level controls with no requirement for prior approval, or 
notification, by the relevant authorities. The flows of recyclables from country to country 
(including both trades within the EU28 and outside it) are thus very difficult to track. 
Furthermore, in many cases, recyclables pass through several countries before reaching their 
final destination, potentially with different operations happening in different countries. 

Efforts to track the amount of green list wastes being sent for recycling have therefore 
tended to rely on trade statistics.28 The trade in wastes has increased significantly since the 
late 1990’s and seems likely to increase as recycling rates continue to improve across 
Member States (Figure 6-1). The limitation of these statistics, however, is that they do not 
differentiate between the origins of the material and therefore do not allow for the accurate 
determination of how much of the traded quantities originates from the municipal waste 
stream. 

Where data on waste exports are reported based on EWC codes, there are fundamental 
problems with the EWC codification system where one seeks to identify which wastes are of 
municipal origin. It is not always possible to know what the municipal waste component is of 
some waste reported under EWC codes covering municipal waste. Also, in general, it is 
impossible to know the amount of municipal waste which is being reported under other, 
more general codes (for example, as packaging waste, which will include both municipal 
packaging and packaging from other sources). 

Viewing the Eurostat data for 2011, waste reported for import / export for R1 treatment 
includes mixed municipal waste alongside a range of waste types seemingly of commercial 
origin (e.g. wood waste, clinical waste).  Therefore, even when the Eurostat data contains 
tonnages reported under the EWC 20 codes, we are not guaranteed usable tonnage data for 
the purpose of modelling the transboundary movement of municipal waste within the 
European Waste Model. 

The second major issue mentioned was that it is not possible to know how much municipal 
waste is being reported under EWC codes outside of those dealing with municipal waste. 
This relates to groups of material type specific codes which do not differentiate between 
sources of the waste. For example: 

“15 — Waste Packaging; absorbents, wiping cloths, filter materials and protective 
clothing not otherwise specified.” 

This waste packaging category contains the subset: 

“15 01 — Packaging (including separately collected municipal packaging).” 

28 See, for example: European Environment Agency (2012) Movements of Waste Across the EU’s Internal and 
External Borders, 2012, www.eea.europa.eu/publications/movements-of-waste-EU-2012 which cites Eurostat 
trade data - Eurostat (2014) International Trade Data: EU trade since 1988 by CN8 (DS_016890), Date Accessed: 
7th July 2014, Available at: 
http://epp.eurostat.ec.europa.eu/portal/page/portal/international_trade/data/database  

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Under this subset are grouped: paper and cardboard packaging (15 01 01), plastic packaging 
(15 01 02), metallic packaging (15 01 04) and so forth. The origin of these material streams is 
not covered in the coding, which gives rise to two closely related problems: 

1)  It is not possible to know what percentage of waste reported under a 15 coding is of 

municipal origin and what percentage is commercial or industrial; and 

2)  It is not possible to know the comprehensiveness of data reported under a 20 coding, 
as municipal material may be, instead, reported under a more general, material 
specific coding. 

Therefore, even if we could be certain that the municipal waste coding referred solely to 
municipal waste, the presence of these other material specific codes would not permit any 
degree of certainty as to the comprehensiveness of the explicitly municipal data. 

Figure 6-1: Exports of Waste Plastics and Selected Waste Metals from EU 
Member States (1999 – 2011) 

Source: European Environment Agency (2012) Movements of Waste Across the EU’s Internal and External 
Borders, 2012, www.eea.europa.eu/publications/movements-of-waste-EU-2012 

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37 

 
 
Data on the import/export of Waste Electrical and Electronic Equipment (WEEE) poses a 
further problem, and it has been stated by the EEA that: 

“WEEE is normally classified as hazardous, implying that the authorities in recipient 
countries must be notified before it is transported across borders, and export to non-
OECD countries is prohibited by the EU's Waste Shipments Regulation (EU, 2006a). 
Exporting fully functional appliances to non-OECD countries is permitted but it can be 
difficult to discern when a used electrical or electronic item is a second-hand product or 
waste. There is little information and data about cross-border movements of WEEE and 
this has negative environmental consequences”.29 

Data on the quantity of used Electrical and Electronic Equipment (EEE) and WEEE is 
therefore very poor.  Article 16(4) of the recast WEEE Directive (Directive 2012/19/EU) 
requires that: 

“Member States shall collect information, including substantiated estimates, on an 
annual basis, on the quantities and categories of EEE placed on their markets, collected 
through all routes, prepared for re-use, recycled and recovered within the Member 
State, and on separately collected WEEE exported, by weight”. 

Member States were required to have transposed Directive 2012/19/EU into national 
legislation by 14th February 2014.30 Thus, assuming full compliance with the data reporting, 
the benefits of improved reporting on the export of WEEE by Member States is only likely to 
materialise from 2015 and will take a few more years before the information appears on 
Eurostat. It is still then unclear if the data will differentiate between WEEE from municipal 
sources vs other sources. Therefore, the reality at present is that the flow of WEEE arising 
from municipal origins cannot readily be included in the Municipal Waste Model.      

Anecdotally, casting further doubt on the comprehensiveness of recycling export data, it is 
common industry practice in the UK to simply leave whole sections of the required shipping 
data forms blank.31 Article 18 of the Transfrontier Shipment of Waste Regulations requires 
all shipments of waste to be accompanied by a fully completed Annex VII form detailing the 
material type being shipped as well as its origin and destination. However, UK industry 
claims that this information is commercially sensitive, and so will frequently refuse to 
provide it. England’s Environment Agency has threatened business engaging in this 
deliberate non-reporting with legal action, but industry body The Recycling Association is 
itself mounting a challenge against Article 18 in the European courts. 

To summarise, there are a number of challenges related to understanding which materials 
destined for recycling are of municipal origin. Not least among these is the structure of the 
EWC waste list, which entails that any tonnage reports employing its codification are 

29 European Environment Agency (2012) Movements of Waste Across the EU’s Internal and External Borders, 
2012, www.eea.europa.eu/publications/movements-of-waste-EU-2012 
30 Directive 2012/19/EU, Article 24(1) 
31 Let’s Recycle (2014) Exporters consider Annex VII legal challenge, Date Published: 31st July 2014, Date 
Accessed: 12th August 2014, Available at: www.letsrecycle.com/news/latest-news/exporters-consider-annex-
vii-legal-challenge/ 

FINAL REPORT 

 
                                                   
 
unusable for the purpose of modelling the transboundary movement of municipal waste to 
the extent that: firstly, it is not known how much reported ‘municipal waste’ is in fact of 
municipal origin; and secondly, it is not known how much municipal waste is being reported 
under more general codes such as those for packaging waste, and so missing from the 
municipal reporting. In addition to this, Member States are not obliged to report on the 
cross-border movement of green list wastes which means that the current data reported to 
Eurostat is far from comprehensive.  

Finally, it should be considered that where there exist end-of-waste criteria for specific 
materials, that material is no longer considered as a waste at all. As such, it is not covered by 
waste legislation and would only be covered through trade data on exports and imports of 
goods. The same problem would arise in respect of defining this as municipal waste (or 
otherwise). 

6.1.3 

Composting 

A 2008 report by the European Commission’s Joint Research Centre / Institute for 
Prospective Technological Studies, which included an assessment of the scale of the 
transboundary movement of compost in the EU, concluded that: 

“…the import and export potential for compost is quite limited. Besides the cross border 
activities related to home markets of compost plants no continued commercial cross 
border compost material flow was detectable.”32 

The low value and universality of composting technologies places limitations on the 
economic viability of importing / exporting compost, though one could conceive of situations 
where the need for organic matter made such export viable. Otherwise, only in cases where 
catchment areas for home markets of facilities straddle Member State borders (for example, 
between the Northern Ireland part of the UK and the Republic of Ireland) is it likely to make 
logistical and economic sense to engage in the transboundary movement of this waste.   

The same report found that with improving composting technologies, some market 
demands could arise for high calibre compost products which would provide economic 
incentives for transboundary movements. However, such high quality products may have 
achieved End of Waste status, and may no longer be considered as waste. Therefore, the 
movement of compostable waste does not represent a significant data source appropriate 
for inclusion in the model.  

6.1.4 

Treatment (Recovery) 

The use of municipal waste as a feedstock for incineration with energy recovery is prevalent 
across much of the EU. Continued heavy investment over a number of years, and the 
introduction of landfill bans, has in some cases resulted in ‘excess’ capacity (i.e. there is 
insufficient waste of a suitable type available in the given Member State to fill the extant 
facilities). In order to avoid the issue of overcapacity a number of Member States have 
looked to sell this capacity to other countries seeking treatment solutions for their residual 

32 European Commission DG JRC/ITPS (2008) Compost production and use in the EU, 2008, 
http://susproc.jrc.ec.europa.eu/activities/waste/documents/080229_EoW_final-report_v1.0.pdf  

28/05/2015 

39 

 
                                                   
 
waste. In this context, it should be noted that the market for export was opened up 
significantly by the setting of the R1 criterion in the 2008 version of the Waste Framework 
Directive. 

Whereas the transboundary movement of separated waste streams for material recovery 
(i.e. recycling) is not subject to a process of notification, this is not the case for energy 
recovery from incineration. The Waste Shipment Regulations —the EU transposition of the 
Basel Convention—states that the transboundary movement of mixed municipal waste shall 
be subject to the same conditions as waste movement for disposal, and therefore requires 
notifications to be made to the competent authority of the country of dispatch. Article 3(5) 
states: 

“Shipments of mixed municipal waste (waste entry 20 03 01) collected from private 
households, including where such collection also covers such waste from other 
producers, to recovery or disposal facilities shall, in accordance with this Regulation, be 
subject to the same provisions as shipments of waste destined for disposal”.33 

Exporting municipal waste for recovery can take one of two routes: 

1)  Material exported as unprocessed mixed municipal waste (EWC 20 03 01);34 or 
2)  As processed refuse derived fuel (EWC 19 12 10).35  

In both instances the movement has to be notified and therefore data should exist on the 
movements of these waste streams.36 However, given that the combustible materials/refuse 
derived fuel (RDF) categorised under EWC 19 12 10 come from waste management facilities 
it is impossible to know what percentage of this waste originally came from municipal 
sources (and is therefore of relevance to the European Municipal Waste Model). Although 
the export of waste as RDF is believed to have increased significantly over recent years, it 
seems entirely possible that it has been facilities processing commercial waste will have 
accounted for the greater part of waste exported for recovery. Furthermore, the available 
Eurostat data is sufficiently dated that this becomes more likely since exports of municipal 
waste for energy recovery are more likely to have followed on from public procurement 
processes, which may take time to complete.  

Given the above discussion it is evident that it is not possible to include within the existing 
model the flow of materials, arising within the municipal waste stream (as defined by 
individual countries) which are exported/imported for recovery at R1 registered facilities. 

6.1.5 

Disposal  

The Waste Framework Directive provides that the EU should handle the environmental 
burden of its own waste disposal, being self-sufficient in disposal capacity. While self-

33 Commission Regulation (EC) No 1013/2006 of the European Parliament and of the Council of 14th June 2006 
on Shipments of Waste, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:02006R1013-20130410 
34 20: Municipal wastes (household waste and similar commercial, industrial and institutional wastes) including 
separately collected fractions; 03: Other municipal wastes; 01: Mixed municipal waste. 
35  19:  wastes from waste management facilities; 12: wastes from the mechanical treatment of waste (for 
example sorting, crushing, compacting, pelletising); 10: combustible waste (refuse derived fuel) 
36 Eurostat (2014) Transboundary Waste Shipments, Date Accessed: 20th August 2014, Available at: 
http://ec.europa.eu/eurostat/c/portal/layout?p_l_id=502398&p_v_l_s_g_id=0 

FINAL REPORT 

                                                   
 
sufficiency is also an expected goal for individual Member States, the transboundary 
movement of waste for disposal within the EU is not legally prohibited. Since waste should, 
in principle, be disposed of at the nearest appropriate installation, it may happen that the 
nearest appropriate installation is located across a border. Also, the requisite treatment 
infrastructure may not exist in the country of origin of the waste, for example, in the case of 
hazardous waste disposal. 

Waste moving across EU borders for the purpose of disposal is subject to notification to the 
competent authority of the country of dispatch under the provisions of the Waste Shipment 
Regulations. This notification requires detailed information on the waste to be exported—
more detailed than the general type of data reported to the European Commission. 
Although detailed export and import data for some countries is available through Eurostat, 
the absence of a legal prescription to report this data at EU level casts doubt on the quality 
of overall data: it is either non-existent, or lacks the certainty which would be delivered by a 
legal imperative.  

Member States’ reports to the European Commission on transboundary movements of 
waste for disposal use the Y-codes of the Basel Convention, while interstate notification to 
competent authorities uses EWC codes. The Y-codes, however, are severely limited in 
application. A 2009 working paper by the European Topic Centre on Sustainable 
Consumption and Production (ETC/SCP) put the matter thus: 

“Low quality data on notified waste is a general problem with the current reporting 
methods. This is partly because the codes of the Basel Convention – the so called y-
codes – do not correspond adequately to the waste streams actually shipped. More 
than one third of the notified waste is not classified according to the codes of the Basel 
Convention mainly because there is no suitable code for the waste. Further, when codes 
can be applied, they are too general to describe exactly what kind of waste is being 
shipped.”37 

In light of the above, the prospect of including the trasboundary movement of municipal 
waste destined for disposal in the European Municipal Waste Model appears to be limited. 

6.2  Approach to Modelling Waste Imports and Exports 

In light of the above data limitations it was agreed with the Commission that there would be 
value in developing a stand-alone tool that could be used for assessing the relative financial 
and environmental costs and benefits of exporting Solid Derived Fuel (SRF) / Refuse Derived 
Fuel (RDF) for recovery at R1 registered facilities. Such a tool was also thought to be of value 
in terms of addressing a comment made in a briefing paper issued by the European 
Parliament in October 2014: 

“… the IA [on the review of EU waste management targets] refers to the potential positive 
impact on the functioning of the internal market of an increase in the transport of 
waste from one Member State to another, but does not assess the environmental 
consequences of such transport. The striking example used to illustrate the acceleration 

37 ETC/SCP (2009) Data availability on the transboundary shipments of waste based on the European Waste List, 
December 2009 

28/05/2015 

41 

 
                                                   
 
of the trend in exporting waste to energy recovery facilities, where waste exports from 
the UK to other EU countries 'passed from few tons in 2010 to more than 1 Million tons 
in 2013' (IA/2, p. 5), would suggest that this is an area which might merit further 
consideration beyond the internal market aspect.”38 

Section 6.2.1 outlines our approach to developing this tool, before providing a case study of 
UK exports to the Netherlands in Section 6.2.2. The case study is intended to provide an 
example of how the Export Tool may be used to assess what the relative costs and benefits 
are of importing/exporting waste between different Member States. Section 6.2.3 briefly 
examines what the key implications are for not accounting for the cross-border movement 
of municipal waste in the Municipal Waste Model.  

6.2.1 

Summary of the Export Tool 

The Export Tool has been developed as an extension to the Municipal Waste Model and is 
contained in a separate Excel document which draws key data directly from the Model. The 
Tool allows users to determine the impacts of exporting waste for treatment from one 
Member State to another. In essence, the model is intended to support decision making and 
allow users to ascertain whether or not there are financial and/or environmental benefits to 
be gained from exporting waste for treatment at incinerators or MBT plants in other 
Member States.  

It is conceivable that users may wish to use the Tool in more than one way: 

1)  They may wish understand what the total costs and benefits to society are for 

importing/export waste (i.e. ignoring prevailing market conditions and historical 
trends); or 

2)  They may wish to assess what overall costs and benefits are of exporting / importing 

waste given current market conditions; or 

3)  They may wish to do both, seeking to understand whether the suite of policies in 
place generates incentives that are compatible with what is best for society 

As described in the technical documentation which accompanies the Municipal Waste 
Model, the unit costs of different treatment technologies are not based on gate fees but 
rather on the resource cost of constructing and operating facilities.39 This is because the tool 
has been developed as a cost-benefit analysis model. Gate fees, on the other hand, are 
dynamic and reflect market conditions, including the balance of supply and demand of the 
desired feedstock. They do not necessarily represent the actual cost of operating a facility.  

While the Export Tool allows for the overall costs and benefits of waste imports and exports 
to be assessed, it can also be used to assess the merits of exporting/importing waste based 
on gate fees. This allows for a more accurate assessment of the likely costs and benefits 
under prevailing market conditions. As shown in Section 6.2.2 the two approaches can lead 

38 European Parliament (2014) Initial Appraisal of a European Commission Impact Assessment: Review of EU 
Waste Management Targets, October 2014 
39 For more details see Appendix 4 of the following report: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment and European Environment Agency, February 
2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

FINAL REPORT 

                                                   
 
to quite different conclusions.     Figure 6-2 outlines the boundaries of the Export Tool and 
demonstrates what elements are included in calculating the financial and environmental 
impacts of managing the waste in its country of origin or in a foreign country. It can be seen 
from this figure that the model calculates the net costs and benefits of disposing/treating 
the waste in the home country, compared to what it would cost (from a financial and 
environmental perspective) to send the material abroad for recovery. The calculation of the 
costs and benefits in each country are taken directly from the Municipal Waste Model and 
include factors such as the following: 

  Capital investment in infrastructure and ongoing operational costs;40 
  Both climate change and air quality impacts;41  
  The operational efficiency of the incinerators;42 and 
  The marginal energy mix of the country (this is important as the benefits of 

power/heat generation will vary depending on the marginal energy source that 
the additional energy production would offset).43 

It is important to note that the Tool does not aim to look at the total impact associated with 
imports and exports of municipal waste between Member States, but focuses exclusively on 
what the impacts would be of exporting, at the margin, an additional tonne of waste (as 
noted above it is not possible, at least given current data reporting, to track cross border 
movements of municipal waste). For specific instances, where a known volume of waste is 
being considered, toolkit users would easily be able to multiply their total tonnages by the 
per tonnage outputs of the Tool.     

The overall structure of the model is shown graphically in Figure 6-3. From this it can be seen 
that the Tool consists of five parts: 

1)  Model set-up – here users are required to define the country where the waste 

originates and the country to which the material will be exported. 

2)  Model assumptions – the model has inputted default assumptions for the 

environmental impacts associated with road transport and shipping in the seas that 
surround Europe (i.e. the model differentiates between impacts that occur in the 
Baltic, Mediterranean, North East Atlantic, and North Sea).  

3)  Data inputs from the European Municipal Waste Model –Member State specific 

baseline data on the financial costs and environmental impacts of treating waste at 
MBT facilities, incinerators, or disposing of the material at landfill sites is fed into the 
Tool from the Municipal Waste Model. By default the Tool extracts unit cost data 
from a single scenario (i.e. the scenario which assesses 70% recycling and preparation 
for reuse target by 2030 – Option 3.1-High). Importing data from different policy 
scenarios was tested, but this has minimal impact on the results as the Tool mostly 

40 See Section 2.0 in Appendix 4 of the following report:  Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment and European Environment Agency, February 
2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
41 See Appendix 6 of the above cited document 
42 See Section 7.3 in Appendix 6  of the above cited document 
43 See Section 2.6 in Appendix 6 of the above cited document 

28/05/2015 

43 

 
                                                   
 
uses unit cost data which is largely unaffected by changes in mass flows. In the future 
toolkit users would be able to update the input data from the Municipal Waste 
Model should this be required.   

4)  Model calculations – the model automatically calculates the financial and 

environmental costs of treating and transporting one tonne of waste based on the 
principles discussed above and outlined in Figure 6-2. 

5)  Model outputs – the model generates the outputs in simple tabular and graphic 

form. 

FINAL REPORT 

 
Figure 6-2: Eunomia’s Export Tool – Accounting for the Costs and Benefits of Exporting Waste for Treatment at Foreign 
Incinerators and/or MBT Plants 

28/05/2015 

45 

Transport to foreign country                                      Treat Waste in Country of OriginExport Waste for TreatmentImpacts of treating /disposing waste incountry of origin LANDFILL or       MBTorINCINERATIONMBT  orINCINERATIONOR€Costsassociated with treatment / disposal CO2Monetiesed climate change  and air quality impacts €Costsassociated with treatment / disposal CO2Monetiesed climate change  and air quality impacts Impactsof treating waste in foreign countryWhere electricity or heat is produced this can offset local productionWhere electricity or heat is produced this can offset local productionNet Costs & Benefits VSNet Costs & BenefitsTheExport Tool calculates the net costs and benefits of treating the waste in the country in which it originates.Net costs and benefits of treating the waste in the country in which it originates can be compared to the net impact of treating it in a foreign country. In this way the pros and cons of each option can be considered more carefully. 
 
Figure 6-3: Overview of the Export Tool 

FINAL REPORT 

It is also worth noting that the model can report the results using a private cost metric or a 
social cost metric. Each of these terms is described in Appendix 4 of the technical 
documentation which accompanies the Municipal Waste Model:44  

  “The ‘Private Metric’ is intended to represent the market conditions from the 

perspective of those undertaking waste operations or those developing and operating 
facilities. It uses retail prices, includes taxes and subsidies, and applies a weighted 
average cost of capital (WACC, typically 10-15% as discussed in Section 1.4 [of 
Appendix 4]) to capital equipment. Taking a treatment facility as an example, this 
approach essentially indicates an approximate ‘break even’ gate fee, inclusive of 
taxes, at a level where the facility would cover its capital and operating costs under 
typical market conditions. 

  The ‘Social Metric’, on the other hand, is appropriate for use in cost benefit analyses 

and impact assessments attempting to calculate an overall cost to society. This metric 
uses the European Commission’s standard 4% discount rate for inter-temporal 
comparisons within impact assessments.45 Subsidies and taxation are also stripped 
away so as to only value the true ‘resource cost’ of an activity. This also avoids any 
double counting of environmental effects that are intended to be internalised within 
environmental taxes and subsidies. Under this metric, environmental damage costs 
can be added to, the financial costs so as to determine, for instance, whether the 
impact of a policy is positive or negative with respect to society”. 

The Tool has been developed in the same format as the European Municipal Waste Model 
and includes step-by-step user instructions on how to set-up and run the Tool. It should 
therefore function as a useful standalone Tool that requires little additional guidance or 
explanation.  

6.2.2 

Case Study: Exports from United Kingdom to the Netherlands 

Over the last number of years the volume of Refuse Derived Fuel (RDF) being exported from 
the United Kingdom (UK) to mainland Europe has increased markedly.46 The rapid increase in 
exports from England and Wales is shown in Figure 6-4. This has raised a number of 
questions about the relative pros on cons of this activity, particularly with respect to the 
environmental impacts.  

To a large extent, the export of RDF has been driven by the annual escalation in the UK’s 
landfill tax over the last number of years (the tax reached a maximum of £80 per tonne - 
€101 per tonne47 - in April 2014 and will now be held constant in real terms). The fact that 

44 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool 
on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment and European Environment Agency, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
45 European Commission (2009) Impact Assessment Guidelines, 15 January 2009, SEC (2009) 92.  
46 Let’s Recycle (2014) RDF Exports Close to Exceeding 2013 Level, Date Published: 22 September 2014, Date 
Accessed: 28 November 2014, Available at: www.letsrecycle.com/news/latest-news/rdf-exports-close-
exceeding-2013-level/  
47 Exchange based on £1 = €0.7955 – exchange rate provided by www.xe.com on 28 October 2014 

28/05/2015 

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the material is being exported suggests that, in the case of the UK, there is a clear financial 
advantage to doing this.  

Figure 6-4: Tonnes of RDF Exported from England and Wales to Europe 
between July 2010 and July 2014 

Source: UK Environment Agency (2014) RDF International Waste Shipments from England and Wales – 
Indicative, Date Accessed: 15 December 2014, Available at: http://data.gov.uk/dataset/rdf-international-waste-
shipments-from-england-and-wales-indicative  

In order to provide an example of the outputs from the Export Tool we used it to illustrate 
what the overall costs and benefits are for shipping waste from the UK to the Netherlands. 
Key assumptions on waste preparation, transport costs, and gate fees are presented in Table 
6-2.  From this it can be seen that the waste preparation and transport costs associated with 
moving waste from the UK to the Netherlands amounts to a total of €46 per tonne.      

Table 6-2: Transport Costs for Exporting Waste from the UK to NL 

Cost Item  

Bulking and Transport Costs 
(€ per tonne) 

Shredding, baling and wrapping 
Transport to UK port 
Shipping from UK to NL 

Total 

Source: Internal data from Eunomia Research & Consulting. 

€21 
€14  
€11  

€46 

The costs shown in Table 6-2 will vary between countries depending on labour costs, fuel 
costs, distances over which waste will be transported and requirements for shipping, road or 
rail haulage etc. Toolkit users are required to input sensible assumptions prior to generating 
the outputs and making interpretations about the net costs and benefits of exporting waste 
for incineration. Many of the input assumptions used here come from Eunomia’s 
understanding of both the UK and Dutch markets and the relative costs of transporting 

FINAL REPORT 

020,00040,00060,00080,000100,000120,000140,000160,000180,000200,000Jul-10Oct-10Jan-11Apr-11Jul-11Oct-11Jan-12Apr-12Jul-12Oct-12Jan-13Apr-13Jul-13Oct-13Jan-14Apr-14Jul-14Oct-14Tonnes of RDF Exported 
waste between the two countries. Should Toolkit users wish to model other countries it will 
be necessary to input reliable assumptions on transport cots, gate fees etc.    

The overall cost of incinerating waste in the UK vs the Netherlands is presented in Table 6-3. 
This table shows the financial and external costs associated with incinerating one tonne of 
waste in each country. If waste is exported to the Netherlands from the UK then an 
additional costs of €51 per tonne will be incurred as a result of transporting the waste. This 
figure includes €46 per tonne of financial costs associated with road haulage and shipping 
(Table 6-2), as well as €5 per tonne from the environmental damages caused by the 
transportation.     

Table 6-3: Net Cost to Society of Incinerating Waste in the UK vs Incineration in 
the Netherlands1 

Cost Item 

Financial costs of incineration (social 
metric) 
External costs 
Transport costs2 
Net Social Costs 
Note: 

Cost of 
Incineration in UK 

Cost of 
Incineration in NL 

Net Cost 
(NL – UK Costs) 

€ per tonne (2015 Real Term Prices) 

€80 

€19 
€0 
€99 

€94 

€16 
€46 
€155 

€14  

-€3 
€46 
€56 

1.  Positive costs denote a cost to society whilst negative costs represent savings/benefits. 
2.  The financial cost of transporting waste by road and ship is €46 per tonne, with an additional external 

cost of €5 per tonne arising from the environmental impacts of the transport. 

A few points can be drawn from the data in Table 6-3: 

  The overall cost of building and operating incinerators is €14 per tonne higher in the 
Netherlands compared to the UK under the social metric (it is worth noting that 
these figures do not represent gate fees); 

  Due to the higher efficiency of Dutch incinerators (e.g. from the use of combined 
heat and power) and differences in the energy mix of the national grid, the 
external/environmental costs of incinerating waste in the Netherlands are €9 per 
tonne lower than in the UK; and 

  The total net social costs of incinerating one tonne of waste in the UK is €99 per 

tonne compared to €104 in the Netherlands. This is a differential of €5 per tonne, 
which rises to a differential of €56 per tonne once transport costs are included.  

The conclusion that can be drawn from this is that there is a net cost to society as a whole 
for shipping waste from the UK to the Netherlands. This conclusion is based on the 
assumption that incineration capacity would have to be built in each country to process the 
waste. As described above, the unit costs of different treatment technologies in the Tool are 
not based on gate fees but rather on the actual cost of constructing and operating 

28/05/2015 

49 

 
 
facilities.48 This is because gate fees, by nature, are dynamic and reflect market conditions. 
They do not represent the actual cost of operating a facility.  

Figure 6-4 shows the rapid increase in the volume of RDF exported from England and Wales 
over recent years. This has occurred precisely because the market dynamics have favoured 
export (Dutch incinerators, for instance, lowered gate fees to such an extent that, even 
including transport, there were savings to be made from treating waste in the Netherlands). 
These market dynamics are not accounted for in the Municipal Waste Model and thus the 
Export Tool has been set up to allow users to make use of gate fee data to assess the overall 
costs and benefits of exporting waste for treatment under current market conditions. This 
functionality is likely to be more useful to waste operators who are wishing to look at the 
options for sending material abroad.  

If one substitutes the financial costs in Table 6-3 with market determined gate fees the 
conclusion that one comes to is quite different. A summary of the key figures is presented in 
Table 6-4. It can be seen that the lower gate fee offered by Dutch incinerators and the higher 
environmental performance (reflected as a lower cost) are sufficient to more than offset 
both the financial and environmental costs of transport. Indeed, when using an 
approximation of current gate fees it would appear that there is a net benefit of €22 per 
tonne to be gained from sending waste to the Netherlands for incineration. The above 
discussion therefore shows that if spare capacity already exists, it makes sense to use it 
rather than to invest in additional capacity, not least because the latter could compound the 
growing problem of overcapacity in certain Member States.  
Table 6-4: Net Cost of Treating Waste in UK vs NL in Current Market1 

Cost Item 

Cost of Incineration 
in UK 

Cost of Incinerating 
in NL 

Net Cost 
(NL – UK Costs) 

Gate fees 
External costs 
Transport costs4 
Total  
Notes: 

€ per tonne (2015 Real Term Prices) 
€1312 
€19 
€0 
€150 

€673 
€11 
€51 
€129 

-€64  
-€9 
€51 
-€22 

1.  Positive costs denote a cost to operators exporting waste under current market conditions whilst 

negative costs represent savings/benefits. 

2.  This is the median UK gate fee reported for facilities built after 2000 – see Urban Mines, and Horne 
Consulting (2014) Gate Fees Report 2014: Comparing the Costs of Alternative Waste Treatment 
Options, Report for Waste & Resources Action Programme, July 2014, 
www.wrap.org.uk/node/24149/. 

3.  Gate fee based on Eunomia’s internal experience of the Dutch market.  
4.  The financial cost of transporting waste by road and ship is €46 per tonne, with an additional external 

cost of €5 per tonne arising from the environmental impacts of the transport. 

48 These unit costs come directly from the Municipal Waste Model. For more details see Appendix 4 of the 
following report: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment and European Environment Agency, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

FINAL REPORT 

                                                   
 
 Perhaps the important ‘constant’ here is that the environmental case for export can be said 
to exist: the issue is whether one is interested in this from the point of policy, or from the 
perspective of an operator seeking to gain the best deal. Operators will be influenced by 
gate fees. It could be argued that if the sum of the gate fee differential and the 
environmental gain is sufficient to justify the costs of transporting the material, then this 
might be appropriate. On the other hand, gate fees are in part influenced by policies that 
seek, to varying degrees in the different Member States, to internalise the environmental 
costs and benefits of incineration. This complicates the picture somewhat since there may 
be double counting of the environmental impacts in the private cost analysis. In practice, 
therefore, operators are likely to simply seek the best financial outcome.  

Ultimately, it could be argued that the main benefit in exporting material lies in ensuring 
that existing assets are not under-utilised. Gate fees have to adjust to ensure this does not 
happen. Somewhat more worrying from a policy perspective would be a situation in which 
explicit or implicit subsidies for incinerators became the source of a significant build-up of 
capacity in countries already known to have a surplus available. For example, if incineration 
facilities are exempted from energy taxes applied to other types of energy generating 
facilities within a Member State, this can significantly increase the revenue which 
incinerators generate from the sale of energy. This allows facilities to offer gate fees at levels 
which would not be supported by a more rational policy. In effect, this becomes a trade 
distorting measure in the waste market.  

6.2.3 

Implications of Excluding Imports/Exports of Residual Waste / 
RDF from the Municipal Waste Model 

In the Municipal Waste Model, the amount of waste currently being landfilled is of the order 
100 million tonnes (2012 figures). There have been various estimates made of the amount of 
waste which is traded within the EU for the purposes of energy recovery. This is generally 
linked to estimates of the capacity surpluses in various countries, and these estimates 
appear to indicate that by 2020 there may be a total surplus capacity of the order 6.6 to 9.3 
million tonnes.49  

In the most extreme cases, the market prices give rise to movements of material that would 
not be justified on grounds of social costs alone. In these cases, as we have seen, the main 
differential is likely to relate to transport costs. On the external cost side, there may be some 
net benefits, with the impacts of additional transport reducing the benefits associated with 
moving waste to facilities at which energy recovery is greater. On the other hand, the 
transport costs considered in the above example are relatively extreme, including haulage by 
road and ship from the UK to another country: many of the cross border movements require 
less by way of double handling, so that the transport costs can be expected, for many 
movements, to be much lower than in the reported example. That having been said, the UK 
is on course to export around 2.5 million tonnes of RDF for recovery in other EU member 
States, although as noted above,, not all of this will be municipal waste.  

In practice, if one assumed: 

49 Tolvik Consulting (2015) RDF Exports: Here for Good? A Report into the Combustible Waste Market in Europe, 
February 2015, www.tolvik.com/reports/  

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  Half of the waste used to fill up excess capacity was municipal waste; and 
  The net social costs of the movement were around €40 per tonne, 

then the model would overstate the net benefits by around £160 million. This can be 
compared with the overall costs and benefits, which amount to around 400 billion under the 
70% MSW reycling scenario in 2030. 

It should be considered that the above case represents a static scenario: in reality, the net 
social costs and benefits of export should be set within a system context. For example, it can 
be argued that the export of RDF from the UK to the Netherlands allows the Netherlands to 
deal more rationally with an excess of capacity for incineration as it seeks to increase 
recycling rates (an argument which has been made by the Dutch waste management 
industry), with the UK retaining flexibility to increase recycling whilst reducing the amount of 
waste sent to landfill. To the extent that these system effects facilitate the achievement of 
higher rates of recycling (and prevent the ossification of the waste management system in 
countries with excess capacity), then because the net social benefits of recycling tend to be 
relatively high (though varying considerably by material), a model which accounted for these 
systemic effects would probably indicate that even under the social cost modelling, exports 
would have relatively small effects on the results.  

It might further be noted that most of this activity has been motivated by a) the introduction 
of landfill bans in many countries (these tend to be the Member States with excess 
treatment capacity) and b) the changes to the existing waste framework Directive 
(2008/92/EC), notably the elaboration of the R1 criterion for energy efficiency, allowing for 
the export of residual waste to facilities which meet this criterion. Most of this trade will 
already be occurring under the full implementation scenario. The extent to which the new 
scenarios being modelled would impact on trade flows is uncertain: indeed, it may be that 
there is very little change in these flows as one moves from full implementation scenarios to 
the scenarios being modelled. To the extent that this could be said to be the case – and it is 
extraordinarily difficult to anticipate how this trade would change under the new scenarios - 
then clearly, the omission of exports and imports from the model becomes even less of a 
concern than the above analysis suggests.  

6.3  Improving Reporting on Imports and Exports of MSW 

The ToR notes that the contractor: 

“…shall propose a set of precise actions to improve data quality on imports/exports of 
municipal waste notably in the light of the draft Commission proposals for the target 
review (notably the establishment of national registries)”. 

As part of the review of targets, the Commission proposed, in the now withdrawn proposal 
for a Directive,50 that the following paragraph be added to Article 35 of the Waste 
Framework Directive:  

50 European Commission (2014) Proposal for a Directive of the European Parliament and of the Council 
Amending Directives 2008/98/EC on Waste, 94/62/EC on Packaging and Packaging Waste, 1999/31/EC on the 
Landfill of Waste, 2000/53/EC on End-of-Life Vehicles, 2006/66/EC on Batteries and Accumulators and Waste 
Batteries and Accumulators, and 2012/19/EU on Waste Electrical and Electronic Equipment, COM(2014)397, 
July 2014, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52014PC0397 

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“Member States shall set up an electronic registry or coordinated registries to record 
data on hazardous waste and, where appropriate, other waste streams, covering the 
entire geographical territory of the Member State concerned. Member States shall use 
the data on waste reported by industrial operators in accordance with the European 
Pollutant Release and Transfer Register set up under Regulation (EC) N° 166/200651”. 
If electronic registries are to play a role in tracking cross-border flows of municipal waste it 
would be necessary for all Member States to adopt such systems for all waste flows, as is 
already done in a number of countries around the world. Europe’s single market provides a 
unique opportunity for trying to develop a singly system that could be integrated across 
Member States, allowing for the cross-border movements of waste to be tracked far more 
easily.  
Eunomia reviewed a number of electronic registries in Appendix 8 of the technical 
documentation which accompanied the Targets Review Project. 52 One of these was the 
European Data Interchange for Waste Notification Systems (EUDIN) which has been set up 
between a select number of EU Member States to track the import and export of waste (Box 
1). Such schemes, if set up correctly, could be used to improve the tracking of waste from 
source to ‘end-destination’ (i.e. the point at which materials are disposed of in landfill or 
reprocessed). Although tracking materials in this way is not free of challenges there are 
some important benefits that such a system could help to address in terms of improving the 
quality of the available data on the imports and exports of municipal waste.   

When setting up electronic registries the primary challenges that will be faced include: 

  Lack of a clear definition of what constitutes municipal waste; 
  Tracking waste movements from source to end-destinations; and 
  Lack of relevant legal frameworks. 

Each of these points is discussed briefly below. 

Box 1: European Data Interchange for Waste Notification Systems (EUDIN) 

The European Data Interchange for Waste Notification Systems (EUDIN) is a: 

“… framework of standardised interfaces, business rules and runtime system components 
that enable the seamless exchange of messages dealing with the transport, receipt and 
recovery/disposal of waste across borders between the Member States of the European 
Union and other interested countries”.53 

In essence, the system is intended to aid the exchange of data between European Member 
States as part of efforts to enable the electronic transposition of the requirements of the Waste 
Shipment Regulations. The EUDIN system was developed through a number of partners which 

51 Note from original text: “Regulation (EC) No 166/2006 of the European Parliament and of the Council of 18 
January 2006 concerning the establishment of a European Pollutant Release and Transfer Register and 
amending Council Directives 91/689/EEC and 96/61/EC (OJ L 033, 4.2.2006, p.1)”. 
52 Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-Institut (2014) Impact 
Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill Directive and 
Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 
53 EUDIN (2014) Facts & Figures, Date Accessed: 11th November 2014, Available at: 
www.eudin.org/ms/eudin/eudin_factsandfigures/  

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include Austria, Belgium, Germany, Luxembourg and the Netherlands. At present it appears as if 
only Belgium, Germany, and Luxembourg are making use of the system and the intention is to 
open up the platform to other Member States in the near future.54 

Figure 6-5: Overview of the EUDIN System 

Source: European Data Interchange for Waste Notification Systems, 
www.eudin.org/ms/eudin/eudin_factsandfigures/ 

6.3.1 

Definition of Municipal Solid Waste 

Eunomia discussed the limitations of the current definition of municipal waste at length as 
part of the Targets Review Project and proposed a potential solution in Appendix 9.55  As 
part of this work a number of possible options were discussed, with a final recommendation 
being made to define municipal waste as follows: 

“Household wastes, and wastes collected from commercial activities which are not part 
of industrial processes covered by NACE codes A to F and class 46.77. 

The definition excludes: waste from the municipal sewage network and treatment, as 
well as waste collected from cleaning of cess pits and other private arrangements for 
sewage services”. 

54 Ibid. 
55 Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-Institut (2014) Impact 
Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill Directive and 
Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

FINAL REPORT 

 
 
                                                   
 
The legislative proposal put forward by the European Commission on the 2nd July 2014, and 
subsequently withdrawn in February 2015, defined municipal waste as follows:  

“Municipal waste includes household waste and waste from retail trade, small 
businesses, office buildings and institutions (such as schools, hospitals, government 
buildings) similar in nature and composition to household waste, collected by or on 
behalf of municipalities. 

It includes: 

o  Bulky waste (e.g. white goods, furniture, mattresses); 
o  Yard waste, leaves, grass clippings, street sweepings, the content of litter 
o  Containers, and market cleansing waste; 
o  Waste from selected municipal services, i.e. waste from park and garden 

maintenance, waste from street cleaning services; 

It also includes waste from the same sources, and similar in nature and composition, 
which: 

o  Are not collected on behalf of municipalities but directly by producer 

responsibility schemes or private non-profit institutions for re-use and 
recycling purposes mainly by separate collection, 

It excludes: 

o  Originate from rural areas not served by a regular waste service. 
o 
o  Waste from sewage network and treatment, including sewage sludge, 
o  Construction and demolition waste”56 

In contrast to Eunomia’s recommendation outlined above, the Commissions proposed 
definition is much narrower stating instead that municipal waste is waste which is 
“collected by or on behalf of municipalities”. As noted in our discussion in Targets Review 
Project this opens up significant variance in what does and does not constitute municipal 
waste in any one country. When trying to identify cross border movements of waste 
based on EWC codes, this ambiguity makes it impossible to know which materials are or 
are not from municipal origins. If it is deemed important to know what cross border 
flows of materials can be identified and classified as municipal waste, then it would seem 
crucial to link the definition of municipal waste to the nature of the reporting systems. 
There are therefore two options: 

1)  Either the definition of MSW has to be link directly to the codes being used to 

report on the import / export of waste; or 

2)  The codes relevant to reporting on the import / export of waste will have to be 

amended to include one or more categories which are aligned with the definition 
of MSW. 

56 See Annex 1 in: European Commission (2014) Proposal for a Directive of the European Parliament and of the 
Council Amending Directives 2008/98/EC on Waste, 94/62/EC on Packaging and Packaging Waste, 1999/31/EC 
on the Landfill of Waste, 2000/53/EC on End-of-Life Vehicles, 2006/66/EC on Batteries and Accumulators and 
Waste Batteries and Accumulators, and 2012/19/EU on Waste Electrical and Electronic Equipment, 
COM(2014)397, July 2014, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52014PC0397 

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6.3.2 

Tracking Municipal Waste Movements – Issues with Mixing and 
Re-export 

As noted in the previous section, the use of EWC codes does not allow for accurate tracking 
of waste streams. Indeed, different facilities along the waste management chain may use 
different codes to define the outputs from their facilities after materials from various 
sources have been mixed together. For example, a municipality may send ‘mixed municipal 
waste’ (20 03 01) for sorting at an MBT plant which then recovers some recyclables (e.g. 
metals) and sends these off as a new (and differently coded) waste stream.  

A graphical example of the mixing of waste streams is presented in Figure 6-6. This figure 
shows how two different waste streams mix and split as they pass from one facility to the 
next. In this example, comingled recyclables collected by, or on behalf of, a municipality 
(yellow blocks) are sent to a primary Material Recovery Facility (MRF) for initial sorting, 
along with waste from other municipal and/or non-municipal sources (green blocks). The 
primary MRF may then apply EWC codes that do not allow the waste to be identified as 
coming from municipal origins (e.g. by using the EWC 15 category for waste packaging).  
Where mixing of municipal waste streams occurs it can be very challenging to track materials 
from one facility/merchant to the next and therefor to know if materials which are being 
exported were originally collected “by or on behalf of municipalities”. As materials pass 
between operators it is also likely that they apply different EWC codes and material may also 
be stockpiled for periods of time when material values are low and this can lead to further 
challenges in tracking materials of municipal origin.     

If an EU wide electronic registry were to be developed it would be necessary (in the absence 
of a clear definition of municipal waste) to devise a mechanism for tracking municipal waste 
to its point of export. Where mixing occurs and waste is sent off to multiple 
facilities/merchants it would be necessary to apply some apportionments in order to 
estimate what proportion of the municipal waste is going where. This is not a 
straightforward process and would require knowledge of the volumes of waste being 
delivered to a facility by different operators so that material losses and outputs could be 
apportioned appropriately based on the volume of incoming material.  The UK’s edoc 
electronic system, for example, allows users of the system to use an optional tracking system 
to follow the fate of one’s waste.57 However, it is not clear exactly how this tracking occurs 
and to what extent it can follow individual materials, such as, plastics, whose pathway 
towards a final reprocessor can be rather complex (by final reprocessor we do not mean the 
point at which it is exported, but rather the point at which it is recycled).58 It is worth noting 
that in many instances – especially where materials are collected separately at source and 
sent directly to final reprocessors – it can be relatively easy to track materials. The example 
given above applies more to materials which require additional sorting and processing 

57 edoc (undated) Electronic Duty of Care: The New Way to Record Waste Transfers, Slide Presentation 
Developed by edoc, http://edoconline.co.uk/resources/edoc-presentation/ 
58 The Article 3(17) of the Waste Framework Directive considers waste to have been recycled when it has been 
“reprocessed into products, materials or substances whether for the original or other purposes.” This is still 
ambiguous in terms of defining when a final reprocessor has been reached, but it is clear it is not the point at 
which waste materials are exported abroad for further reprocessing.  

FINAL REPORT 

                                                   
 
before they are sent to a final reprocessor, or where materials pass through multiple hands 
on their way to their end destination.          

Figure 6-6: Hypothetical Example of the Mixing and Movement of Waste 
Materials Sent for Recycling and the Assignment of EWC Codes 

6.3.3 

Setting up a Legal Reporting Framework 

There is currently no legal obligation to report on ‘green list wastes’ and this would have to 
be revisited if reliable data were to be obtained on the cross border movements of municipal 
(and similar) waste. Alternatively, the mandatory use of electronic data reporting systems 
would ensure that these data were captured. It is likely that there would have to be some 
concession for waste that passes through multiple ports, as it would be very difficult to 

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57 

Keymaterial lossesmaterial lossesmaterial lossesmaterial lossesetc.FinalProductsPrimary Reprocessor and/or MerchantSecondary MRFPrimmary MRFFinal ReprocessorThese  materials are sent on to other reprocessors/merchants where they are mixed with other waste streams before reaching their 'end destination'Waste collected by or on behalf of municipalitiesMaterial outputs/productsOther material streamsMaterial inputs to facilityReject and process losses 
 
 
ascertain the final destination of the material. Data on these exports would also help to 
better understand the extent to which the EU is moving towards a circular economy by 
allowing a better understanding of the quantity of secondary raw materials that are retained 
within Europe for reprocessing. By tracking materials to their end destinations it should also 
be possible to determine the volume of material being reprocessed via open- and closed-
loop recycling processes.       

FINAL REPORT 

 
 
7.0  Updates to the Municipal Waste Model 

In addition to the technical changes which were made to the Municipal Waste Model (see 
discussion in Section 2.1) a number of structural changes were also made. These are briefly 
outlined here to demonstrate completion of the tasks set out in the project’s Terms of 
Reference.   

7.1  General Structural Changes 

The earlier version of the model repeated calculations for each of the 28 Member States. 
This created a very large model that took a long time to run when assessing different target 
scenarios. In order to streamline the model VBA macros were developed to perform 
repetitive calculations. This significantly reduced the size of the model and helped to 
increase its overall stability. 

In addition, the model was split into two separate files: 

1)  EURM_MSWM – Controls and Outputs.xlsm; and 
2)  EURM_MSWM – Calculations.xlsm. 

The Controls and Outputs file contains the user interface and allows users to run the model 
and generate a standalone date stamped output file. The Calculations file, on the other 
hand, is linked to the first document and performs all of the model calculations. The above 
actions have substantially reduced the overall size of the model.  

The model has two modes in which it can be used: 

1)  Admin mode – this allows expert users to access and change any element of the 

model; and 

2)  User mode – under this mode a model user can only access the User Interface. 

The two modes are intended to allow for the model to be shared with non-expert users who 
will not have editing rights.  

7.2  User Interface 

A User Interface (UI) was developed in order to improve the usability of the model and make 
it more accessible to a wider audience. The UI provides step-by-step instructions of how the 
model can be used and leads users through the process of setting up and running different 
policy scenarios and sensitivity tests. The UI has been designed to allow the model to be 
used in isolation without cross referencing to external guidance documents etc.  

By way of example, Figure 7-1 and Figure 7-2 present two screenshots from the UI which 
uses a consistent format throughout. Figure 7-1 shows the ‘Setup Model’ page which allows 
users to identify which country they will be working on and provides a step-by-step outline 
of the process that needs to be followed in order to setup and run different policy scenarios. 
Figure 7-2 provides an example of a typical sheet in the UI with user instructions presented 
down the left hand side to explain what each of the input parameters are and what process 
needs to be followed. Where necessary, text boxes have been included to provide additional 
details on key terms and concepts that are used in the model.  

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Figure 7-1: Setup Model Page 

Navigation 
menu  

Figure 7-2: Waste Arisings Projections Page 

Drop down 
list  

Table containing 
summary details 
about the sheet  

Country Name 

Step-by-step 
instructions 

FINAL REPORT 

 
  
 
7.3  Interactive Tools 

The Terms of Reference for the project required that four “interactive tools” be developed 
for the Municipal Waste Model. The following tools have been integrated into the UI: 

1)  Tool for testing different municipal waste targets; 
2)  Eurostat data conversion tool;  
3)  Waste prevention tool; and 
4)  Sensitivity test tool. 

In the UI policy scenarios are defined in the ‘Set up Policy Scenarios’ tab and users can 
choose to set preparation for reuse and recycling targets as well as targets relating to 
various forms of residual waste treatment or disposal. Users are able to set separate targets 
for different years and can also include selected waste prevention initiatives. A screenshot of 
this tool is provided in Figure 7-3. The tab includes a hyperlink to additional guidance and 
provides clear instructions on how to set up different policy scenarios within the model (the 
model is able to save up to ten different scenarios). 

Figure 7-3: Integrated Tool to Define Policy Scenarios  

As suggested by the name, the Eurostat data conversion tool allows model users to convert 
Eurostat waste data into a format that is consistent with that used in the model (i.e. one 
which accounts for waste sent to MBT). An explanation of the tool and guidance on how to 
use it are provided within the UI under the ‘Annual Update’ tab. This tool allows model users 
to update the waste flow data on an annual basis as new data becomes available (Figure 
7-4). 

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Figure 7-4: Integrated Eurostat Data Conversion Tool 

The integrated sensitivity test tool enables model users to assess the sensitivity of the model 
outputs to key assumptions. See Section 3.0 above for a discussion of the set of assumptions 
that have been included in this tool and examples of the outputs that are generated. A 
screenshot of the tool is provided in Figure 7-5. 

Figure 7-5: Integrated Sensitivity Test Tool 

The waste prevention tool allows for the selection of up to ten different waste prevention 
initiatives. For each of the initiatives that are selected users are required to input key 
assumptions about the scale of the initiative and the likely financial investments. A 

FINAL REPORT 

   
  
screenshot of the tool, with the ‘say no to unsolicited mail’ initiative selected, is shown in 
Figure 7-6.   

Figure 7-6: Integrated Waste Prevention Tool 

7.4  Model Guidance 

The Terms of Reference for the project state: 

“It is also expected from the contractor to develop as appropriate user guidance for 
the modules where a need has been identified during the training or in the course of 
the contract period and/or if needed (if gaps are identified) to complete the already 
existing documentation describing and referencing all assumptions to ensure the full 
transparency of the model (at least 10 man days to be reserved).” 

It was agreed between the EEA and the European Topic Centre on Waste Management and 
the Green Economy (ETC) that the guidance should be incorporated within the model itself. 
This was felt to be the best approach as it eliminates the need to switch between different 
documents and means that the guidance can be accessed via hyperlinks at the point of use. 
Efforts were therefore invested in developing integrated guidance rather than producing a 
separate guidance document. 

It was agreed that the guidance should:  

1)  Provide some detailed guidance for key technical elements of the UI; 
2)  Include references for key sources of data and assumptions within the model; 
3)  Use text boxes to explain each of the calculation tables included within the 

‘EURM_MSWM – Calculations.xlsm’ file;  

4)  Provide a navigation tool for moving around the model; and 
5)  Include flow charts to explain how the various calculation sheets are interlinked.  

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An example of explanatory guidance that has been included in the UI is shown in Figure 7-7 
(this guidance relates to the Eurostat data converter). This, and other, guidance is accessed 
directly via hyperlinks contained within the UI and is used to provide further details and 
explanations of key concepts and processes.  

Figure 7-7: Example Guidance Included in the User Interface   

In order to facilitate easy navigation around the ‘EURM_MSWM – Calculations.xlsm’ file a 
navigation panel was developed. This panel is shown in Figure 7-8 which shows the different 
sheets associated with the ‘Waste Flow Calculations’ module. User can press on any of the 
buttons to access the relevant sheets that make up this module. The tab across the top 
allows user to access worksheets in other modules (e.g. ‘Waste Prevention Module’ or 
‘Collections Module’). When in sheets that contain calculations users can press the ‘Current 
Sheet’ button at the top of the panel to access a flow diagram which relates to the particular 
sheet. An example of such a flow diagram is presented in Figure 7-9. These flow diagrams 
show which sheets the active/current sheet is linked to (i.e. where the inputs are coming 
from and where the outputs from the sheet are going to). Again, the buttons in this flow 
diagram act as hyperlinks that can direct users to the relevant input and output sheets. This 
functionality has greatly improved navigation around the model, with individual flow 
diagrams having being produced for close on a hundred different sheets.  

FINAL REPORT 

 
 
Figure 7-8: Navigation Pane in the Calculations File 

Figure 7-9: Example of Flow Diagram with Hyperlinks 

View sheets in 
other modules  

Buttons with hyperlinks to 
sheets within each module 

Sheets that link to the 
current sheet 

Current sheet being viewed / 
edited by model user 

Sheets to which the 
current sheet outputs 
results 

To explain the overall structure of each module flow diagrams are provided in all black 
coloured tabs which are positioned at the start of each module. An example of the ‘Waste 
Flow Calculations’ flow diagram is presented in Figure 7-10.  This diagram shows how the 

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module links with other areas of the model and can help users understand the complex 
interactions between the different areas of the model. 

Figure 7-10: Example of Overview Flow Diagram 

Given the size and complexity of the model the integrated guidance, flow diagrams, and 
navigational tools took a substantial amount of time and effort to develop. However, it is 
believed that this additional functionality is important and greatly improves the overall 
usability of the model. As noted above, the available budget was invested in producing 
integrated guidance rather than standalone documentation. There may still be value, 
however, in producing standalone guidance for different users as a means of further 
enhancing the usability of the model (e.g. developing separate guidance for Member States, 
non-expert user, or for more advanced users).  

FINAL REPORT 

 
 
 
 
8.0  Dissemination of the Results 

As part of this contract Eunomia was requested to assist the Commission and the European 
Environment Agency with disseminating the results of the work undertaken as part of the 
project. The Terms of Reference required that:    

“The contactor shall participate to seminars, conferences aiming at ensuring the 
dissemination of the results and at increasing the confidence in the model. This will 
include the participation at least 5 events organised by the Commission or by the EEA in 
principle in Brussels or Copenhagen or exceptionally in another EU MS.” 

Under this task Eunomia attended the EEA expert workshop on the Municipal Waste Model 
in Copenhagen on the 26th and 27th of March 2015.  The workshop introduced the Municipal 
Waste Model to Member State representatives and provided a practical training exercise.  
Eunomia was not required to attend any additional seminars or conferences and it was 
therefore agreed with the Commission that the time allocated for this task in the original 
proposal submitted to the Commission would be used to provide additional training, and 
technical support (see Section 9.0).    

Under this task Eunomia was also required to maintain the website which had been set up 
for the original modelling project (www.wastemodel.eu). The website was updated to 
explain that the model was undergoing further development during the course of 2014 and 
2015 as part of this new contract. The website was handed over to the EEA in late 2014 and 
is now under their control.     

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9.0  Training and Technical Support  

An important aspect of this project was providing training and technical support on the 
Municipal Waste Model. In accordance with the Terms of Reference two training sessions 
were delivered: 

  22nd and 23rd September 2014; and 
  19th, 26th and 27th May 2015. 

The first trainings session provided a detailed introduction to the model, with presentations 
being provided by various members of the project team who had been responsible for 
developing different elements of the model. This training session was held over two days 
and was delivered to the EEA and members of the project team at the European Topic 
Centre on Waste Management and the Green Economy (ETC). The second round of training 
consisted of one-to-one sessions with relevant team members from the ETC. These sessions 
examined different areas of the model in more detail and were focused on building up a 
clear understanding of the nuts and bolts of individual modules.   

The Terms of Reference for the project required that ten days be reserved for responding to 
questions and comments from the EEA and ETC in relation to the Municipal Waste Model. In 
addition to a number of technical questions numerous comments on the model were also 
received. A log of these comments and the actions taken is presented in Appendix A.4.0. 
Many of the comments required that additional elements be added to the model which had 
not been stipulated in the Terms of Reference. Responding to questions and addressing 
these comments took substantially longer than the 10 days allocated in the original 
proposal.  Time was therefore reallocated from the ‘Dissemination of the Results’ task 
discussed above to ensure that more effort could be invested in improving the model.       

FINAL REPORT 

 
 
LIST OF APPENDICES 

Prepared as separate documents. 

A.1.0  C&D Model Overview 

A.2.0  C&D Waste Model – Member State Summary 

Reports 

A.3.0  Municipal Waste Model – Member State Summary 

Reports 

A.4.0  Log of Actions Taken on the Municipal Waste Model 

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FURTHER DEVELOPMENT OF 
THE EUROPEAN REFERENCE 
MODEL ON WASTE 
GENERATION AND 
MANAGEMENT 

FINAL REPORT – APPENDIX 1: 
CONSTRUCTION AND DEMOLITION WASTE 
MODEL 

Dr Dominic Hogg 

Thomas Vergunst 

Laurence Elliott 

28th May 2015 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Report for Michel Sponar, DG Environment of the European Commission 

Prepared by Thomas Vergunst and Laurence Elliott 

Approved by  

Dr Dominic Hogg 

(Project Director) 

Eunomia Research & Consulting Ltd 
37 Queen Square 
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Disclaimer 

Eunomia Research & Consulting has taken due care in the preparation of this report to 
ensure that all facts and analysis presented are as accurate as possible within the 
scope of the project. However no guarantee is provided in respect of the information 
presented, and Eunomia Research & Consulting is not responsible for decisions or 
actions taken on the basis of the content of this report. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

1.0 

Introduction ......................................................................................................... 1 

1.1  Overview of C&D Model ............................................................................................... 1 

1.2  Appendix Structure ....................................................................................................... 1 

2.0 

Inputs and Assumptions ....................................................................................... 2 

2.1  Baseline Waste Data ..................................................................................................... 2 

2.1.1  Waste Arisings and Treatment Destinations ......................................................... 2 

2.1.2  Waste Composition ................................................................................................ 2 

2.1.3  Waste Growth Rates .............................................................................................. 4 

2.2 

Environmental Impacts ................................................................................................. 5 

2.3 

Employment Impacts .................................................................................................... 7 

3.0 

Approach to Collections and Waste Treatment ..................................................... 9 

3.1  Collections Assumptions ............................................................................................... 9 

3.1.1 

Collection Systems .................................................................................................. 9 

3.1.2  Material Densities ................................................................................................ 11 

3.2 

Fixed Hire and Collection Costs .................................................................................. 11 

3.3  Disposal Costs ............................................................................................................. 12 

3.3.1  Gate Fees .............................................................................................................. 12 

3.3.2  Material Revenues ............................................................................................... 12 

4.0 

Modelling Scenarios ........................................................................................... 14 

4.1 

Scenario Specification ................................................................................................. 14 

4.2 

Scenario Controls ........................................................................................................ 14 

5.0 

Key Uncertainties Associated with the Model ..................................................... 16 

APPENDIX 1  

iii 

 
 
 
 
List of Tables, Figures and Boxes 

Table 2-1: List of Sources used for Composition Data ............................................................... 3 

Table 2-2: C&D Waste Compositions for Modelling .................................................................. 4 

Table 2-3: Environmental Assumptions ..................................................................................... 6 

Table 2-4: Employment, Number of Full Time Equivalents (FTEs) per Thousand Tonnes of 

Waste Processed ................................................................................................................. 8 

Table 3-1: Collections Systems ................................................................................................ 10 

Table 3-2: Percentages of Each Material within the Mixed and Separated Waste Fractions . 10 

Table 3-3: Material Densities ................................................................................................... 11 

Table 3-4: Fixed Hire/Collection Costs, € per Container per Collection (UK) .......................... 11 

Table 3-5: Division of Fixed Hire/Collection Costs ................................................................... 12 

Table 3-6: Gate Fees (Before Disposal Tax), € per Tonne ........................................................ 12 

Table 3-7: Revenues from the Sale of Recyclables .................................................................. 13 

Table 4-1: Modelling Parameters by Group and Scenario ....................................................... 15 

iv 

28/05/2015 

 
 
 
1.0  Introduction 

The Terms of Reference (ToR) of this project required that a construction & demolition 
(C&D) waste model be developed with three scenarios included. This Appendix provides an 
overview of the C&D Model and identifies key sources of data and assumptions that have 
been used to generate the results presented in Section 2.0 of the main report and the 
Member State summary reports in Appendix A2.0.  

1.1  Overview of C&D Model 

The C&D Waste Model enables a better understanding of the management and treatment 
of C&D waste in each of the 28 Member States (or the EU28 as a whole). The model is based 
on a simplified version of the Municipal Waste Model (from which it draws many of its 
assumptions), and can be used to quantify the impact of different scenarios in respect of 
financial impacts,  impacts on the environment, job creation, greenhouse gas emissions. It 
thereby allows for the overall costs and benefits of different scenarios to be calculated out 
to 2035. 

1.2 

Appendix Structure  

As noted above, this Appendix provides more information on the technical details of the 
C&D Waste Model. The following sections are included: 

1)  Section 2.0 – provides information on the assumptions used in the model, setting 
out the data sources used and any methods used to estimate unknown data; 

2)  Section 3.0 – details the approach used for collection and treatment modelling, and 

lists all the assumptions used for these calculations; 

3)  Section 4.0 – provides more information on modelling scenarios and how new 

scenarios can be set-up by the user; and 

4)  Section 5.0 – details the main mass flow uncertainties in the model. 

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1 

 
 
 
2.0 

Inputs and Assumptions 

2.1 

Baseline Waste Data 

For each Member State, the following data were required to project forward the arisings 
and treatment destinations for each C&D waste stream: 

1)  A database of current C&D arisings and treatment destinations (see Section 2.1.1); 
2)  A full breakdown of C&D waste compositions (see Section 2.1.2); and 
3)  Growth rates of C&D waste (see Section 2.1.3). 

The sources of information and assumptions used to obtain the above information is 
summarised below.    

2.1.1  Waste Arisings and Treatment Destinations 

Construction and demolition waste generation and treatment tonnage data used in the 
model were sourced from Eurostat waste statistics (EWC-Stat 12.1).1,2 All waste data in the 
model is based on Eurostat waste code W121: “mineral waste from construction and 
demolition”. 

The model has been set up with 2010 and 2012 waste data and therefore forward 
projections currently start from the year 2013. 2011 data was not available as Eurostat only 
publish data on C&D waste arisings once every two years. It was assumed that waste 
arisings and treatment tonnages in 2011 were equal to the average of the values published 
by Eurostat for 2010 and 2012. The model user is provided with a straightforward user 
interface to update waste data as and when it becomes available from Eurostat.  

2.1.2  Waste Composition 

Government statistics published by each Member State as well as other data sources were 
used to compile an approximate compositional breakdown of C&D waste arisings for each 
country. An extensive search of publically available literature revealed that these data vary 
considerably in both quality and usability. A sifting process was therefore required in order 
to select the most appropriate data sources for inclusion in the model. During this selection 
process, the rationale was to always choose country data from the most recent year for 
which it was available, and to discard obviously inaccurate or oversimplified data (e.g. a 
percentage breakdown of 50% soil and 50% mineral waste with no other waste streams 
given). We used a sample of the remaining data sources (listed in Table 2-1) to identify 
common compositional themes across Member States and thereby establish two sets of 
C&D waste composition data (shown in Table 2-2). 

1 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
2 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
                                                      
 
Table 2-1: List of Sources used for Composition Data 

Country and Year of Data 

Data Source 

Austria 2004 

The Federal Ministry for Agriculture, Forestry, Environment and Water1 

Denmark 2005-2006 

Ministry of the Environment2 

England 2010 

Department for Environment Food & Rural Affairs3 

Estonia 2005-2006 

Statistics Estonia4 

Finland 2004 

Germany 2011 

VTT Technical Research Centre of Finland5 

Federal Statistical Office6 

Netherlands 2005-2006 

European Topic Centre on Sustainable Consumption and Production7 

Wales 2005-2006 

StatsWales8 

Source: 

1.  The Federal Ministry for Agriculture, Forestry, Environment and Water (2011) Bundes-

Abfallwirtschaftsplan, December 2011, http://www.bundesabfallwirtschaftsplan.at/ 

2.  Ministry of the Environment (2013) ISAG database, Accessed 15th November 2013, 

http://www2.mst.dk/databaser/isag/Default.asp?help=Yes 

3.  Department for Environment Food & Rural Affairs (2013) Waste Prevention Programme for England: 

Call for Evidence, March 2013, 
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/221130/wpp-
consult-doc-20130311.pdf 

4.  Statistics Estonia (2013) Statistical Database: Waste Balance by Waste Categories, Accessed 15th 

November 2013, http://pub.stat.ee/px-
web.2001/Dialog/varval.asp?ma=EN610&ti=WASTE+BALANCE+BY+WASTE+CATEGORIES&path=../I_D
atabas/Environment/01Environmental_pressure/06Generation_of_waste/&lang=1 

5.  VTT Technical Research Centre of Finland (2006) Expert Study to Support Building Waste Statistics of 

the Year 2004 

6.  Federal Statistical Office (2013) Waste Balance, July 2013, 

https://www.destatis.de/EN/FactsFigures/NationalEconomyEnvironment/Environment/Environmental
Surveys/WasteManagement/Tables/WasteBalance2011.pdf?__blob=publicationFile 

7.  European Topic Centre on Sustainable Consumption and Production (2009), EU as a Recycling Society: 

Present Recycling Levels of Municipal Waste and Construction and Demolition Waste in the EU, April 
2009, http://scp.eionet.europa.eu/publications/wp2009_2/wp/WP2009_2 

8.  StatsWales (2013) Construction and Demolition Waste by Component and Measure, Accessed 15th 
November 2013, https://statswales.wales.gov.uk/Catalogue/Environment-and-Countryside/Waste-
Management/Construction-and-Demolition-Waste/ConstructionAndDemolitionWaste-by-Component-
Measure 

The two compositional sets (Table 2-2) were calculated by averaging the compositional data 
from two distinct groups of Member States, defined primarily on the basis of mineral waste 
and wood contents. During this process we made a number of simplifications to account for 
the fact that data for some waste streams (wood, glass, metals, plastics and gypsum) are 
either not present, or are available but only at a more aggregated level. Data for these 
waste streams were not available for one country (Estonia) in the ‘High Wood’ 
compositional set. In this case more aggregated data were available and the quantities of 

28/05/2015 

3 

 
each material were calculated using the assumption that the relative proportions of these 
materials were the same as for the Welsh data, for which a comprehensive breakdown was 
available.3 Similarly, we lacked any data on these same materials for two countries 
(Germany and the Netherlands) within the ‘High Mineral Waste’ compositional set. In this 
case we assumed that the ‘High Mineral Waste’ compositional set had the same percentage 
arisings of these waste streams as was reported for Wales.4 

Table 2-2: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass  Metals  Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste1 

3.34%  0.07% 

1.46% 

0.91% 

1.38%  36.96% 

51.41%  4.46% 

High Wood2 

Notes: 

26.0% 

0.1% 

9.4% 

1.5% 

2.3% 

30.6% 

24.1% 

6.0% 

1.  This compositional set was applied to the following member states: AT, BE, BG, CY, CZ, DE, DK, EL, ES, 

FR, HR, HU, IE, IT, LT, LU, LV, MT, NL, PT, RO, SI, SK, UK 

2.  This compositional set was applied to the following member states: EE, FI, PL, SE 

An assessment was made of the most appropriate compositional set to assign to each 
country. This was done by referring back to the country-specific compositional breakdowns 
collected during initial data gathering, and comparing these with each compositional set. In 
the case that data was not available for a specific country we assigned compositional sets 
based on information from qualitative sources.  

2.1.3  Waste Growth Rates 

The model requires future projections for C&D waste arisings and treatment tonnages in 
each Member State. Our review of the literature found no existing forecasts, requiring us to 
create our own projections. A review of historical Eurostat data demonstrates that, in most 
cases, C&D waste growth is linked with economic (i.e. GDP) growth. This is not surprising 
considering that the performance of the construction sector is generally viewed as a 
significant factor in the overall health of a country’s economy. 

Our approach to estimating future projections for C&D waste assumes that, for any given 
year, the growth in C&D waste is equivalent to the product of GDP growth and a ‘growth 
multiplier’. We assume that wealthier Member State, defined as those whose GDP exceeds 
the EU28 average, will have a multiplier of 0.5 (i.e. C&D waste will grow at a rate equivalent 

3 StatsWales (2013) Construction and Demolition Waste by Component and Measure, Accessed 15th November 
2013, https://statswales.wales.gov.uk/Catalogue/Environment-and-Countryside/Waste-
Management/Construction-and-Demolition-Waste/ConstructionAndDemolitionWaste-by-Component-
Measure 
4 Ibid.  

 
 
                                                      
 
to half of the GDP growth rate).5 For less wealthy Member States a multiplier of 1.0 in 2013 
is used, and this is assumed to decrease at a constant rate over time to a final rate of 0.5 
from 2020 onwards.6 Our rationale for this assumption is that with continued progress 
towards more resource efficient behaviour these Member States will experience a gradual 
decoupling of C&D waste growth and GDP over time.  

These assumptions are concordant with a previous study conducted for WRAP, which found 
that, as GDP per capita increases, waste growth will become progressively decoupled from 
GDP growth and at a certain level of GDP per capita will begin to decrease.7 It therefore 
seems fair to assume that more wealthy countries will have a lower multiplier (i.e. C&D 
waste arisings will grow at a slower rate than GDP). It should be noted that the conclusion 
reached by the WRAP study was for household waste only – the authors state that it was 
not possible to analyse C&D waste due to a lack of quality data. It seems unlikely that C&D 
waste arisings will actually begin to decrease once a certain GDP per capita is reached, as 
the WRAP study reported for household waste. It is more probable that, as countries 
become wealthier, C&D waste growth will slow down relative to GDP growth, but still 
demonstrate an overall increase. 

2.2 

Environmental Impacts 

The model assesses the environmental benefits between a ‘comparison’ and baseline 
scenario. Three types of impacts are analysed: 

1)  Climate change impacts are considered in isolation (as tonnes of CO2 equivalent); 
2)  The combined impact of both the climate change impacts together with those 

impacts associated with other emissions to air such as NOx, SOx, and PM. Pollutant 
impacts are given a monetary value, such that the outcome can be considered in € 
(the Member State specific monetary value of these impacts are based on those 
used in the Municipal Waste Model); and 

3)  Avoided disamenities, both from the reduced extraction of primary aggregates/soils 
and minerals when materials are recycled (i.e. the disbenefits associated with living 
in the vicinity of a quarry) and from landfilling/backfilling (i.e. the disbenefits 
associated with living in the vicinity of a landfill). 

A range of environmental assumptions are required to quantify the unit environmental 
external costs, associated with switching from landfilling, backfilling or incineration to 
recycling. For example, for a given material, the unit environmental cost associated with 
decreased greenhouse gas emissions (due to a switch from incineration to recycling) can be 
calculated in the following manner: 

5 The following Member States are defined as ‘more wealthy’: Austria, Belgium, Denmark, Finland, France, 
Germany, Ireland, Italy, Luxembourg, Netherlands, Sweden, and the United Kingdom. 
6 The following Member States are defined as ‘less wealthy’: Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, 
Greece, Hungary, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Slovakia, Slovenia, and Spain.  
7 Bio Intelligence Service, Metroeconomica & Resource Futures (2012) Decoupling of Waste and Economic 
Indicators, Report for WRAP, October for 2012, 
http://www.wrap.org.uk/sites/files/wrap/Decoupling%20of%20Waste%20and%20Economic%20Indicators.pdf 

28/05/2015 

5 

 
                                                      
 
Unit Environmental Cost (€/tonne) = Carbon Cost * [ - ( direct emissions from 
incineration + energy use + energy generation benefits ) + recycling impacts] 

Table 2-3 lists the full range of environmental assumptions used for modelling. The source 
of these data can be found in Appendix A6.0 of the technical documents associated with the 
European Reference Model on Municipal Waste Management.8 Additional sources were 
required for gypsum data and for disamenity assumptions, these latter data were sourced 
from the study used to influence the level of the UK aggregates levy.9,10 The unit 
environmental costs calculated using these assumptions are presented in the Member State 
summary reports which are included in Appendix 2. 

Table 2-3: Environmental Assumptions 

Assumption Type 

Name 

Units 

Recycling - Climate 
Change Impacts 

Recycling - Air Quality 
Impacts 

Avoided Emissions (Excluding Biogenic CO2) 

Tonnes CO2 Equivalent per Tonne 
of Material Recycled 

Air Quality Damage Costs 

€ per Tonne of Material Recycled 

Recycling - Avoided 
Disamenity 

Avoided Disamenity from Reduced Extraction 
of Primary Aggregates/Soils and Minerals 

€ per Tonne of Material Recycled 

Incineration Inputs by Type 

% of Total Incineration 

Incineration - Climate 
Change Impacts 

Direct Emissions from Incineration Process 

Tonnes CO2 Equivalent per Tonne 
of Material Incinerated 

Emissions from Energy Used During 
Incineration Process 

Tonnes CO2 Equivalent per Tonne 
of Material Incinerated 

Emissions Avoided Through Energy 
Generation 

Tonnes CO2 Equivalent per Tonne 
of Material Incinerated 

Air Quality Damage Costs 

€ per Tonne of Material 
Incinerated 

Incineration - Air 
Quality Impacts 

Emissions from Energy Used During 
Incineration Process 

€ per Tonne of Material 
Incinerated 

Damage Cost for Emissions Avoided Through 
Energy Generation 

€ per Tonne of Material 
Incinerated 

8 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool 
on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment and European Environment Agency, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
9 ERM and Golder Associates (2008) Life Cycle Assessment of Plasterboard, Report for WRAP, April 2008 
10 London Economics (1999) The Environmental Costs and Benefits of the Supply of Aggregates, Phase 2, 
Report for DETR, July 1999. 

 
                                                      
 
Assumption Type 

Name 

Units 

Landfill - Climate 
Change Impacts 

Damage Cost for Direct Emissions from 
Process 

€ per Tonne of Material Landfilled 

Damage Cost for Emissions Avoided Through 
Energy Generation 

€ per Tonne of Material Landfilled 

Emissions Avoided Through Energy 
Generation 

Tonnes CO2 Equivalent per Tonne 
of Material Landfilled 

Total Climate Change Impacts 

Tonnes CO2 Equivalent per Tonne 
of Material Landfilled 

Landfill - Air Quality 
Impacts 

Damage Cost for Direct Emissions from 
Process 

€ per Tonne of Material Landfilled 

Damage Cost for Emissions Avoided Through 
Energy Generation 

€ per Tonne of Material Landfilled 

Landfill/Backfill - 
Disamenity 

Avoided Disamenity from 
Landfilling/Backfilling 

€ per Tonne of Material 
Landfilled/Backfilled 

The C&D Waste Model uses the EEA value for the carbon damage cost out to 2029. After 
this point, the model bases its damage cost assumptions on the price projections given in 
the latest iteration of the EU-ETS and provided to Eunomia by DG Clima. These projections 
suggest that the cost of each EU Allowance unit (EUA) to be €35 in 2030 and €57 in 2035. 
For values after 2035 (used in the modelling of future landfill emissions) the model allows 
for impacts to be calculated using a fixed value of €57, or a declining impact based on the 
application of the Commission’s discount rate of 4%. 

Two further assumptions were required. Firstly, it was assumed that the climate change and 
air quality impacts for switching from backfilling to recycling were zero. Only inert materials 
can be used for backfilling and the recycling benefits are negligible for these materials. 
Moreover, it is unclear whether the diversion of waste from backfill to recycling leads to a 
decrease in primary resource extraction. Secondly, given that there is relatively little 
available data for the recycling impacts from aggregates (in terms of greenhouse gas 
emissions) we instead used similar data for glass as a proxy. The exact figure used relates to 
crushed glass which is used as a replacement for aggregates, i.e. a similar final product. 
Furthermore, the energy use for either system to produce either product should be similar 
(i.e. negligible). 

2.3 

Employment Impacts 

The impacts of different waste management scenarios on employment can be estimated in 
the model. This calculation assumes that a set number of Full Time Equivalents (FTEs) are 
required for the collection, reprocessing and treatment of a unit of waste, varying according 
to the final treatment destination. The relative differences in treatment destinations 
between scenarios can then be used to calculate the change in the number of FTEs. 
Assumptions on the number of FTEs used in modelling are presented in Table 2-4. These are 

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7 

 
 
derived from the Municipal Waste Model, supported by industry information and Eunomia 
waste collection and treatment data. 

Table 2-4: Employment, Number of Full Time Equivalents (FTEs) per Thousand 
Tonnes of Waste Processed 

Treatment Type 

Landfill 

Incineration 

Backfill 

Recycling 

Waste Type 

Number of Jobs 

All 

All 

All 

Wood 

Glass 

Metals  

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.25 

0.25 

0.25 

0.6 

0.6 

5.9 

7.2 

0.8 

0.3 

0.3 

0.3 

 
 
 
3.0  Approach to Collections and Waste 

Treatment  

The C&D Waste Model is structured around a number of waste collection and treatment 
systems, each representing a different route for a particular waste type as it passes from 
collection through to disposal. Three systems are defined for mixed waste, differentiated by 
their primary treatment destination: landfill, backfill, and recycling. A further seven systems 
define the route from separate collection to recycling for each waste type. Recycling in the 
model can therefore take place via two pathways: 

1)  Mixed waste is collected in skips and taken to   a sorting centre for subsequent 

sorting and recycling; and 

2)  Separate collection of each waste stream using a number of different container 

types. 

Based on the financial cost and collection assumptions, the model calculates a unit cost for 
each of these systems, representing the total cost of collection and disposal per tonne of 
waste. These unit costs are combined to calculate the unit cost of switching treatment 
options, from backfill, incineration, and landfill to recycling. The total cost of switching 
treatment options when moving from the baseline to a comparison scenario can then be 
calculated based on the change in the overall flow of materials. 

3.1 

Collections Assumptions 

3.1.1 

Collection Systems 

The collection systems used in the model are listed in Table 3-1. The container types listed 
here are commonly used throughout Europe; however, the model user may wish to modify 
these assumptions if different containers are used in specific Member States.  

It is assumed that, when recycling is the primary treatment option for a skip collection, 75% 
of the waste contained within a mixed skip is recycled. Data published by WRAP in 2009 
indicates recovery rates from C&D material recovery facilities (MRFs) operating at that time 
were reported by site operatives to be from 75-98%; similar performance data was noted on 
websites of skip operators currently in operation.11 It is anticipated that recycling rates will 
be slightly lower than this, given that a significant proportion of wood waste is combusted 
rather than being recycled. As such, the 75% figure is felt to be indicative of the typical 
recycling performance of such sites. 

For most materials, the recycling performance of separately collected material describes the 
proportion of uncontaminated material presented at reprocessors (i.e. the proportion of 
material that is not rejected). The exception here is wood, for which the recycling 
performance is assumed to be relatively low (70%). This reflects the fact that a significant 
volume of separately collected wood is disposed of via incineration. The values used for 

11 Oakdene Hollins (2009) Good Practice in Construction and Demolition Materials Recovery Facilities, Final 
Report for WRAP, October 2009 

28/05/2015 

9 

 
                                                      
 
these assumptions reflect the typical recycling performances observed at European 
reprocessors. However, the user should adjust these figures if required to provide a more 
accurate representation of country specific performances. 

Table 3-1: Collections Systems 

Waste Type 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Notes: 

Container Type 

8 yard skip (6.1 m3) 

Disposal 
Type 

Landfill 

8 yard skip (6.1 m3) 

Incineration 

8 yard skip (6.1 m3) 

Backfill 

8 yard skip (6.1 m3) 

Recycling 

Building Bags (0.75 m3) 

Recycling 

660L bin 

Recycling 

240L bin 

Recycling 

Building Bags (0.75 m3) 

Recycling 

Building Bags (0.75 m3) 

Recycling 

8 yard skip (6.1 m3) 

Recycling 

8 yard skip (6.1 m3) 

Recycling 

Recycling 
Performance1 

- 

- 

- 

75% 

70% 

90% 

95% 

90% 

75% 

95% 

95% 

1.  The recycling performance is effectively a total loss rate for all post-collection sorting and 

reprocessing. Waste that is not recycled is assumed to go to landfill. 

Construction sites demonstrate considerable variability in their approach to dealing with 
C&D waste. Not all sites are able to accommodate the segregation of waste into large 
numbers of skips / bays / bins / bags. On-site sorting is therefore more prevalent at larger 
construction sites. The percentages for each material within both the mixed and separate 
waste fractions are displayed in Table 3-2. 

Table 3-2: Percentages of Each Material within the Mixed and Separated Waste 
Fractions 

Material 

Percentage of Material in Mixed 
Collections 

Percentage of Material in Separate 
Collections 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

45.5% 

46.8% 

43.3% 

98.8% 

98.0% 

23.2% 

23.2% 

54.5% 

53.2% 

56.7% 

1.2% 

2.0% 

76.8% 

76.8% 

Source: Eunomia (2010) Site Waste Management Plans Cost Benefit Analysis, Report for Welsh Assembly 
Government, July 2010 

 
 
3.1.2 

Material Densities 

Material density values used in the model are displayed in Table 3-3. Material densities are 
a major determining factor for the overall collection cost. This is mainly because the number 
of collections required to collect a tonne of low density material, such as plastic, is much 
greater than for higher density materials, such as soil. It is also assumed that containers are 
filled to 85% of capacity at the point of collection. 

Table 3-3: Material Densities 

Material 

Mixed Waste1 
Wood2 
Glass2 
Metals1 
Plastics2  
Gypsum1 
Soil1 
Mineral Waste and Asphalt1 

Sources:  

Un-compacted bulk density (tonnes/m3) 

0.87 

0.6 

1.2 

0.42 

0.05 

0.33 
1.25 
1.24 

1.  WRAP (2010) Material Bulk Densities, Summary report, 

http://www.wrap.org.uk/sites/files/wrap/Bulk%20Density%20Summary%20Report%20-
%20Jan2010.pdf 

2.  Eunomia (2010) Site Waste Management Plans Cost Benefit Analysis, Report for Welsh Assembly 

Government, July 2010 

3.2 

Fixed Hire and Collection Costs 

The fixed hire and collection costs used in the model are listed in Table 3-4. Due to a lack of 
data availability for collection costs in most European Member States, the model uses fixed 
hire/collection costs for the UK to calculate prices for all other Member States. 

Table 3-4: Fixed Hire/Collection Costs, € per Container per Collection (UK) 

Material  

Skip1 

Building Bags 

660L bin2 

240L bin2 

Mixed Waste 
Wood 
Glass 
Metals 
Plastics  
Gypsum 
Soil 
Mineral Waste and Asphalt 

Sources:  

€ 160 

€ 160 
€ 160 

€ 18 

€ 18 
€ 18 
€ 18 
€ 18 

€ 9 

€ 8 

1.  Eunomia (2010) Site Waste Management Plans Cost Benefit Analysis, Report for Welsh Assembly 

Government, July 2010 

2.  Prices are from a commercial waste service managed for a confidential client 

28/05/2015 

11 

 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
Prices are prorated according to the relative difference in transport costs (diesel prices) and 
labour costs (mean gross annual earnings) between the UK and each Member State.12 Table 
3-5 presents our assumptions for the split of the total fixed hire/collection costs between 
labour costs, transport costs, and other costs. These assumptions represent our expert 
judgement based on previous collections modelling experience. 

Table 3-5: Division of Fixed Hire/Collection Costs 

Labour  

Fuel 

Other 

Skip 

Building Bags 

660L bin 

240L bin 

25% 

30% 

45% 

40% 

27% 

33% 

18% 

6% 

76% 

20% 

7% 

73% 

3.3 

Disposal Costs 

3.3.1 

Gate Fees 

Gate fees are charged for a range of waste disposal options. For this study it was necessary 
to estimate the gate fees charged by landfill and incinerator operators. Gate fee prices are 
difficult to obtain, not least because this data is often viewed as commercially confidential. 
Most studies of gate fees require a large number of interviews to be conducted with local 
authorities and sorting facilities to obtain cost data.  

The gate fee cost assumptions used in the model are presented in Table 3-6. These 
assumptions are prudent estimates of average gate fees in the EU28 based on our 
professional expert judgement. It is also assumed that a backfill preparation cost of €1.50 
per tonne applies to backfilled waste. Users are encouraged to adjust these values to reflect 
the unique situation of each country. 

Table 3-6: Gate Fees (Before Disposal Tax), € per Tonne 

Waste Type 

Disposal Type 

Gate Fee, € per Tonne 

Municipal Waste 

Inert Waste 

Landfill 

Incineration 

Landfill 

Backfill 

€ 2 

€ 2 

€ 2 

€ 0 

3.3.2 

Material Revenues 

The modelled revenues generated on material sent for recycling are listed in Table 3-7. 
Positive values indicate that revenue is raised from the sale of secondary materials, while 

12 Eurostat (2015) Annual Net Earnings [earn_nt_net], Accessed 9th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=earn_nt_net&lang=en; Eurostat (2015) Tax Rate 
[earn_nt_taxrate ], Accessed 9th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=earn_nt_taxrate&lang=en 

 
  
 
 
                                                      
 
negative values specify that the seller bears a cost during this transaction. These values are 
indicative of those generated over recent years, though it goes without saying that these 
fluctuate over time.  

These cost figures are also highly generic and in reality will vary across different markets in 
Europe. For example, there is generally a cost involved with disposing of wood waste; 
however, for countries with a large number of biomass plants, requiring significant wood 
input, it is possible for operators to obtain a revenue/income from their wood waste.  

The negative price for gypsum is mostly due to the saturation of gypsum markets with 
cheap synthetic gypsum which is very pure.13 Recycled gypsum contains a fair amount of 
contaminants and therefore is not preferred in the market. However, secondary gypsum 
could become more competitive in the future if there is less cheap coal available (the raw 
material required for the production of synthetic gypsum). 

Table 3-7: Revenues from the Sale of Recyclables 

Material 

Mixed Waste 

Wood1 

Glass2 

Metals2 

Plastic2 

Gypsum3 

Mineral Waste and Asphalt 

Sources:  

Recycling Revenue, € per Tonne 

€ 0 

-€ 10 

€ 0 

€ 100 

€ 100 

-€ 18 

€ 0 

1.  Eunomia (2015) Comparing the Costs of Alternative Waste Treatment Options, Report for WRAP, April 

2015 

2.  Letsrecycle (2015) Prices, Accessed 20th April 2015, http://www.letsrecycle.com/prices 
3.  Environment Agency (2013) Partial Financial Impact Assessment of a Quality Protocol for the 

production and use of gypsum from waste plasterboard, March 2013 

1. 

13 Environment Agency (2013) Partial Financial Impact Assessment of a Quality Protocol for the production and 
use of gypsum from waste plasterboard, March 2013 

28/05/2015 

13 

 
  
 
 
                                                      
 
4.0  Modelling Scenarios 

4.1 

Scenario Specification 

The C&D Waste Model can be used to model up to four distinct scenarios, the first two of 
which can be used either as the ‘baseline’ or ‘comparison’ scenario. While the user has the 
option to modify all scenarios, three of these scenarios have already been defined, these 
are: 

1)  Business as usual – Under this scenario it is assumed that recycling and backfilling 
are held constant at 2012 rates (the latest year for which data was available at the 
time the model was developed); 

2)  Full implementation – This scenario assumes that Member States meet the Waste 

Framework Directive target of 70% recycling and backfilling by 2020; and 
3)  More ambitious target – This is similar to the full implementation scenario, 

however, this scenario does not allow Member States to use backfilling to meet the 
70% recycling target. 

These scenarios are set-up to meet the requirements set out in the project’s Terms of 
Reference.  

The ‘business as usual’ scenario represents a conservative estimate of future waste 
management in Member States, and, as described above, assumes that 2012 rates are held 
constant for future years. Consideration was made as to whether historical trends could be 
identified and projected forward to enable a more accurate portrayal of future waste 
management in Member States; however, this option is limited by the availability of data. 
Eurostat only publish C&D waste data for two years which does not allow for the 
discernment of a reliable historical trend, although it would be possible to update the model 
in future as more data is published. Further refinement of this scenario would require 
significant primary research - that is, interviews with Member State representatives and 
private sector operators – in order to define country specific trends based on Member State 
intentions. Research of this scale is beyond the scope of this study and is instead being 
covered by a separate contract which has been let by the Commission in recent months. 

A further scenario named ‘user defined’ is left free for model users to set up according to 
their own specifications. Under this scenario the user has the option to modify the future 
projections for recycling and backfilling rates and can choose whether or not backfilling is 
included in the recycling rate calculation. 

4.2 

Scenario Controls 

Each scenario can be set up using one of three control methods: ‘set 2020 rates’, ‘fixed 
increase per annum’ and ‘dynamic scenarios’. The ‘set 2020 rates’ control method asks the 
user to specify fixed recycling and backfilling rates for 2020, while for the ‘fixed increase per 
annum’ control method recycling and backfilling rates are set to increase by a fixed interval, 
specified by the user, each year until 2020. Both of these control methods apply the same 
parameters to all Member States. 

Most users will wish to use the ‘dynamic scenarios’ control method. The user specifies the 
recycling rate target in 2020 and whether or not this includes backfilling. If backfilling is 

 
included, the user is asked to input a maximum backfilling rate, while if it is not included, 
the user must specify the maximum percentage reduction in backfilling that is permissible in 
the model.14 The model then calculates 2020 recycling and backfilling rates taking into 
account the current waste management situation in each Member State. Recycling rates 
between the latest year of data in the model and 2020 are then calculated based on a linear 
projection. 

The functioning of the ‘dynamic scenarios’ control method is illustrated for the ‘Full 
Implementation’ and ‘More Ambitious’ scenarios in Table 4-1. In this table the 2020 
recycling and backfilling rates, relative to current rates, used by the model for forward 
projections are presented for both scenarios. These calculations assume a maximum 
backfilling rate of 15% when backfilling is included in the target. 

Table 4-1: Modelling Parameters by Group and Scenario 

Current Rates for 
Member State 

Recycling and Backfilling Rates in 2020 (Relative to Current Rates) 

Full Implementation 

More Ambitious Target 

Recycling rate 
above 70% 

No change to recycling rate. No change to 
backfilling rate. 

No change to recycling rate. No 
change to backfilling rate. 

Combined recycling 
and backfilling rate 
above 70% 

No change to recycling rate. No change to 
backfilling rate. 

Fixed percentage reduction in 
backfilling. This tonnage of material 
is now recycled. 

Combined recycling 
and backfilling rate 
below 70% 

Current backfilling rate below 15% and recycling 
rate above 55%: Backfilling rate increased to 
70% minus recycling rate; no change to recycling 
rate. 

Current backfilling rate below 15% and recycling 
rate below 55%: backfilling rate increased to 
15%; recycling rate increased to 55%. 

Current backfilling rate above 15%: no change to 
backfilling rate; recycling rate increased to 70% 
minus backfilling rate. 

Fixed percentage reduction in 
backfilling. This tonnage of material 
is now recycled. Recycling rate is 
raised to 70%. 

14 Full guidance on how these backfilling controls operate is included in the model. 

28/05/2015 

15 

 
 
 
 
                                                      
 
5.0  Key Uncertainties Associated with the 

Model   

The C&D Waste Model is a relatively high-level model, and is intended to provide a general 
overview of future C&D waste management scenarios in Europe. In comparison to the 
Municipal Waste Model, a more simplified approach was taken to modelling the movement 
of waste from the point of collection to the final treatment destination. This simplified 
approach was necessitated by the fact that the data on C&D waste is far less robust and the 
contractual scope of this modelling exercise set out in the project’s Terms of Reference was 
much smaller.  

The main mass flow uncertainties, whether these are due to a simplified approach, or to a 
lack of data availability, are summarised below: 

1)  Waste Tonnage Input Data - All waste generation and treatment tonnage data is 
based on Eurostat waste code W121 (“mineral waste from construction and 
demolition”). This creates a discrepancy between the compositions used in the 
model, which include other materials such as metal and plastics, and the 
composition of this input data, which only include mineral waste. In future, more 
accurate data which includes all the materials used in modelling could be gathered 
by liaising directly with Member States; 

2)  Waste Compositions – As discussed in Section 2.1.2, one of two generic 

compositional sets, which were compiled based on a review of C&D composition 
data in Europe, are assigned to each country. Future work could improve the 
accuracy of these data by communicating with Member States to obtain unique C&D 
waste compositions; 

3)  Waste Growth Rates – These are discussed in Section 2.1.3, but in essence a 

simplified approach had to be taken based on GDP growth given the lack of accurate 
time series data on C&D waste in Member States; 

4)  Landfill/Incineration Rates - The model assumes that, in all scenarios, the 

proportion of residual waste sent to landfill and incineration remains the same as in 
the baseline year (the latest year for which data is available). This is a simplifying 
assumption of the model. In reality, for a scenario in which the recycling rate 
increases over time, more waste would probably be diverted from landfill. It is often 
not possible to divert waste from incineration plants to recycling if these plants are 
already constructed and long-term contracts which require a minimum tonnage of 
waste per annum are already in place; and 

5)  Collections Systems – it is assumed that all Member States use the same collection 
systems for C&D Waste. Future model developers may consider defining a unique 
set of collection systems for each Member State. This would require in-depth 
research and discussion with C&D waste experts in Member states, and is outside 
the scope of this current project. 

 
FURTHER DEVELOPMENT OF 
THE EUROPEAN REFERENCE 
MODEL ON WASTE 
GENERATION AND 
MANAGEMENT 

FINAL REPORT – APPENDIX 2: 
CONSTRUCTION AND DEMOLITION WASTE 
MEMBER STATE SPECIFIC REPORTS 

Dr Dominic Hogg 

Thomas Vergunst 

Laurence Elliott 

25th May 2015 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Report for Michel Sponar, DG Environment of the European Commission 

Prepared by Thomas Vergunst and Laurence Elliott 

Approved by  

Dr Dominic Hogg 

(Project Director) 

Eunomia Research & Consulting Ltd 
37 Queen Square 
Bristol 
BS1 4QS 

United Kingdom 

Tel: +44 (0)117 9172250 
Fax: +44 (0)8717 142942 

Web: www.eunomia.co.uk 

Disclaimer 

Eunomia Research & Consulting has taken due care in the preparation of this report to 
ensure that all facts and analysis presented are as accurate as possible within the 
scope of the project. However no guarantee is provided in respect of the information 
presented, and Eunomia Research & Consulting is not responsible for decisions or 
actions taken on the basis of the content of this report. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

1.0 

2.0 

3.0 

Austria ................................................................................................................. 1 

Belgium ............................................................................................................... 2 

Bulgaria ............................................................................................................... 3 

3.1  Waste Generation and Management Projections ........................................................ 4 

3.1.1  Waste Flow Projections .......................................................................................... 4 

3.1.2 

Recycling and Backfill Projections .......................................................................... 4 

3.1.3 

Residual Waste Management ................................................................................ 5 

3.1.4 

Summary of Waste Treatment Destinations ......................................................... 5 

3.2 

Financial Costs .............................................................................................................. 6 

3.3 

Environmental Costs ..................................................................................................... 8 

3.4 

Summary of Costs and Benefits .................................................................................. 10 

4.0 

Croatia ............................................................................................................... 12 

4.1  Waste Generation and Management Projections ...................................................... 13 

4.1.1  Waste Flow Projections ........................................................................................ 13 

4.1.2 

Recycling and Backfill Projections ........................................................................ 13 

4.1.3 

Residual Waste Management .............................................................................. 14 

4.1.4 

Summary of Waste Treatment Destinations ....................................................... 14 

4.2 

Financial Costs ............................................................................................................ 15 

4.3 

Environmental Costs ................................................................................................... 17 

4.4 

Summary of Costs and Benefits .................................................................................. 19 

5.0 

Cyprus ............................................................................................................... 21 

5.1  Waste Generation and Management Projections ...................................................... 22 

5.1.1  Waste Flow Projections ........................................................................................ 22 

5.1.2 

Recycling and Backfill Projections ........................................................................ 22 

5.1.3 

Residual Waste Management .............................................................................. 23 

5.1.4 

Summary of Waste Treatment Destinations ....................................................... 23 

5.2 

Financial Costs ............................................................................................................ 24 

5.3 

Environmental Costs ................................................................................................... 26 

5.4 

Summary of Costs and Benefits .................................................................................. 28 

6.0 

Czech Republic ................................................................................................... 30 

6.1  Waste Generation and Management Projections ...................................................... 31 

6.1.1  Waste Flow Projections ........................................................................................ 31 

APPENDIX 2  

iii 

 
6.1.2 

Recycling and Backfill Projections ........................................................................ 31 

6.1.3 

Residual Waste Management .............................................................................. 32 

6.1.4 

Summary of Waste Treatment Destinations ....................................................... 32 

6.2 

Financial Costs ............................................................................................................ 33 

6.3 

Environmental Costs ................................................................................................... 35 

6.4 

Summary of Costs and Benefits .................................................................................. 37 

7.0 

8.0 

9.0 

Denmark ............................................................................................................ 39 

Estonia ............................................................................................................... 40 

Finland ............................................................................................................... 41 

9.1  Waste Generation and Management Projections ...................................................... 42 

9.1.1  Waste Flow Projections ........................................................................................ 42 

9.1.2 

Recycling and Backfill Projections ........................................................................ 42 

9.1.3 

Residual Waste Management .............................................................................. 43 

9.1.4 

Summary of Waste Treatment Destinations ....................................................... 43 

9.2 

Financial Costs ............................................................................................................ 44 

9.3 

Environmental Costs ................................................................................................... 46 

9.4 

Summary of Costs and Benefits .................................................................................. 48 

10.0 

France ................................................................................................................ 50 

10.1  Waste Generation and Management Projections .................................................. 51 

10.1.1  Waste Flow Projections .................................................................................... 51 

10.1.2 

Recycling and Backfill Projections..................................................................... 51 

10.1.3 

Residual Waste Management .......................................................................... 52 

10.1.4 

Summary of Waste Treatment Destinations .................................................... 52 

10.2 

Financial Costs ......................................................................................................... 53 

10.3 

Environmental Costs ............................................................................................... 55 

10.4 

Summary of Costs and Benefits .............................................................................. 57 

11.0 

Germany ............................................................................................................ 59 

12.0 

Greece ............................................................................................................... 60 

12.1  Waste Generation and Management Projections .................................................. 61 

12.1.1  Waste Flow Projections .................................................................................... 61 

12.1.2 

Recycling and Backfill Projections..................................................................... 61 

12.1.3 

Residual Waste Management .......................................................................... 62 

12.1.4 

Summary of Waste Treatment Destinations .................................................... 62 

12.2 

Financial Costs ......................................................................................................... 63 

iv 

28/05/2015 

 
12.3 

Environmental Costs ............................................................................................... 65 

12.4 

Summary of Costs and Benefits .............................................................................. 67 

13.0 

Hungary ............................................................................................................. 69 

13.1  Waste Generation and Management Projections .................................................. 70 

13.1.1  Waste Flow Projections .................................................................................... 70 

13.1.2 

Recycling and Backfill Projections..................................................................... 70 

13.1.3 

Residual Waste Management .......................................................................... 71 

13.1.4 

Summary of Waste Treatment Destinations .................................................... 71 

13.2 

Financial Costs ......................................................................................................... 72 

13.3 

Environmental Costs ............................................................................................... 74 

13.4 

Summary of Costs and Benefits .............................................................................. 76 

14.0 

Ireland ............................................................................................................... 78 

15.0 

Italy ................................................................................................................... 79 

16.0 

Latvia ................................................................................................................. 80 

17.0 

Lithuania ............................................................................................................ 81 

18.0 

Luxembourg ....................................................................................................... 82 

19.0  Malta ................................................................................................................. 83 

19.1  Waste Generation and Management Projections .................................................. 84 

19.1.1  Waste Flow Projections .................................................................................... 84 

19.1.2 

Recycling and Backfill Projections..................................................................... 84 

19.1.3 

Residual Waste Management .......................................................................... 85 

19.1.4 

Summary of Waste Treatment Destinations .................................................... 85 

19.2 

Financial Costs ......................................................................................................... 86 

19.3 

Environmental Costs ............................................................................................... 88 

19.4 

Summary of Costs and Benefits .............................................................................. 90 

20.0 

Netherlands ....................................................................................................... 92 

21.0 

Poland ............................................................................................................... 93 

21.1  Waste Generation and Management Projections .................................................. 94 

21.1.1  Waste Flow Projections .................................................................................... 94 

21.1.2 

Recycling and Backfill Projections..................................................................... 94 

21.1.3 

Residual Waste Management .......................................................................... 95 

21.1.4 

Summary of Waste Treatment Destinations .................................................... 95 

21.2 

Financial Costs ......................................................................................................... 96 

21.3 

Environmental Costs ............................................................................................... 98 

APPENDIX 2  

v 

 
21.4 

Summary of Costs and Benefits ............................................................................ 100 

22.0 

Portugal ........................................................................................................... 102 

23.0 

Romania .......................................................................................................... 103 

23.1  Waste Generation and Management Projections ................................................ 104 

23.1.1  Waste Flow Projections .................................................................................. 104 

23.1.2 

Recycling and Backfill Projections................................................................... 104 

23.1.3 

Residual Waste Management ........................................................................ 105 

23.1.4 

Summary of Waste Treatment Destinations .................................................. 105 

23.2 

Financial Costs ....................................................................................................... 106 

23.3 

Environmental Costs ............................................................................................. 108 

23.4 

Summary of Costs and Benefits ............................................................................ 110 

24.0 

Slovakia ........................................................................................................... 112 

24.1  Waste Generation and Management Projections ................................................ 113 

24.1.1  Waste Flow Projections .................................................................................. 113 

24.1.2 

Recycling and Backfill Projections................................................................... 113 

24.1.3 

Residual Waste Management ........................................................................ 114 

24.1.4 

Summary of Waste Treatment Destinations .................................................. 114 

24.2 

Financial Costs ....................................................................................................... 115 

24.3 

Environmental Costs ............................................................................................. 117 

24.4 

Summary of Costs and Benefits ............................................................................ 119 

25.0 

Slovenia ........................................................................................................... 121 

26.0 

Spain ............................................................................................................... 122 

26.1  Waste Generation and Management Projections ................................................ 123 

26.1.1  Waste Flow Projections .................................................................................. 123 

26.1.2 

Recycling and Backfill Projections................................................................... 123 

26.1.3 

Residual Waste Management ........................................................................ 124 

26.1.4 

Summary of Waste Treatment Destinations .................................................. 124 

26.2 

Financial Costs ....................................................................................................... 125 

26.3 

Environmental Costs ............................................................................................. 127 

26.4 

Summary of Costs and Benefits ............................................................................ 129 

27.0 

Sweden ............................................................................................................ 131 

28.0 

United Kingdom ............................................................................................... 132 

vi 

28/05/2015 

 
 
1.0  Austria 

According to Eurostat, the C&D recycling rate for Austria was 92% in 2012.1,2 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

1 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
2 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

1 

 
 
 
                                                      
 
2.0  Belgium 

According to Eurostat, the C&D recycling rate for Belgium was 98% in 2012.3,4 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

3 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
4 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
3.0  Bulgaria 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 3-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €105 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 3-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 37.1 

-€ 29.3 

-€ 66.4 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

28/05/2015 

3 

 
 
                                                      
 
 
3.1 

Waste Generation and Management Projections 

3.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.5,6 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 3-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 3-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

742 

488 

793 

522 

834 

548 

876 

576 

921 

606 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
Bulgaria. We therefore proceeded to undertake a qualitative assessment of waste 
compositions in Bulgaria and judged that a ‘High Mineral Waste’ composition would be 
most appropriate (Table 3-3). 

Table 3-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

3.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 3-4 and Table 
3-5. 

5 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
6 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
Table 3-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

12.44% 

34.03% 

21.58% 

12.44% 

70.00% 

57.56% 

12.44% 

70.00% 

57.56% 

12.44% 

70.00% 

57.56% 

12.44% 

70.00% 

57.56% 

Table 3-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

3.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 3-6 and Table 3-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 3-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

1.78% 

1.34% 

-0.44% 

1.78% 

0.61% 

-1.17% 

1.78% 

0.61% 

-1.17% 

1.78% 

0.61% 

-1.17% 

1.78% 

0.61% 

-1.17% 

Table 3-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

85.78% 

64.63% 

-21.15% 

85.78% 

29.39% 

-56.39% 

85.78% 

29.39% 

-56.39% 

85.78% 

29.39% 

-56.39% 

85.78% 

29.39% 

-56.39% 

3.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 3-8.  

Table 3-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

61 

0 

9 

418 

65 

0 

9 

447 

68 

0 

10 

470 

72 

0 

10 

494 

75 

0 

11 

520 

28/05/2015 

5 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

166 

365 

384 

403 

424 

0 

7 

315 

105 

0 

-2 

-103 

0 

3 

153 

300 

0 

-6 

-294 

0 

3 

161 

316 

0 

-6 

-309 

0 

4 

169 

332 

0 

-7 

-325 

0 

4 

178 

349 

0 

-7 

-342 

Figure 3-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
mostly offset by a decrease in landfill, as well as a slight reduction in incineration.  

Figure 3-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

3.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 3-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

 
 
 
 
Table 3-9: Waste Collection and Treatment Unit Costs (2015 Real Term Prices), 
€ per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 27.02 

€ 27.02 

€ 26.52 

€ 25.52 

€ 30.75 

€ 17.93 

-€ 0.04 

€ 28.10 

€ 26.29 

€ 19.37 

€ 19.48 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 3-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 3-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

28/05/2015 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

€ 0.00 

€ 0.00 

€ 0.00 

€ 4.21 

-€ 0.32 

€ 0.00 

€ 0.00 

€ 0.00 

€ 14.81 

-€ 0.81 

€ 0.00 

€ 0.00 

€ 0.00 

€ 15.56 

-€ 0.85 

€ 0.00 

€ 0.00 

€ 0.00 

€ 16.36 

-€ 0.89 

€ 0.00 

€ 0.00 

€ 0.00 

€ 17.19 

-€ 0.94 

-€ 18.18 

-€ 31.38 

-€ 32.98 

-€ 34.66 

-€ 36.43 

€ 0.33 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 2.04 

-€ 0.13 

€ 0.95 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 5.81 

€ 0.99 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 6.11 

€ 1.05 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 6.42 

€ 1.10 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 6.75 

-€ 0.41 

-€ 0.43 

-€ 0.45 

-€ 0.48 

-€ 23.50 

-€ 44.12 

-€ 46.37 

-€ 48.74 

-€ 51.22 

-€ 0.19 

-€ 0.14 

-€ 0.56 

-€ 0.39 

-€ 0.59 

-€ 0.41 

-€ 0.62 

-€ 0.43 

-€ 299.11 

-€ 889.54 

-€ 934.92 

-€ 982.61 

Mineral Waste and Asphalt 

-€ 444.56 

Other C&D 

-€ 35.83 

-€ 
1,213.50 
-€ 103.23 

-€ 
1,275.40 
-€ 108.49 

-€ 
1,340.46 
-€ 114.03 

-€ 0.65 

-€ 0.46 
-€ 
1,032.73 
-€ 
1,408.84 
-€ 119.84 

7 

 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Total 

-€ 819 

-€ 2,262 

-€ 2,378 

-€ 2,499 

-€ 2,627 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

3.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 3-11. These costs reflect the combined impact of both the 
climate change impacts together with those impacts associated with other emissions to air 
such as NOx and PM. 

Table 3-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 32.13 

€ 32.13 

€ 32.13 

€ 33.73 

€ 45.49 

-€ 10.11 

-€ 10.11 

-€ 10.11 

-€ 10.31 

-€ 11.82 

-€ 98.81 

-€ 98.81 

-€ 98.81 

-€ 107.41 

-€ 170.50 

-€ 30.89 

-€ 30.89 

-€ 30.89 

-€ 36.51 

-€ 77.72 

-€ 61.74 

-€ 70.89 

-€ 83.94 

-€ 102.11 

-€ 124.11 

-€ 5.22 

-€ 5.22 

-€ 5.22 

-€ 5.29 

-€ 5.82 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 55.44 

-€ 55.44 

-€ 55.44 

-€ 58.83 

-€ 83.65 

-€ 6.68 

-€ 8.80 

-€ 8.80 

-€ 8.80 

-€ 6.68 

-€ 8.80 

-€ 8.80 

-€ 8.80 

-€ 6.68 

-€ 8.80 

-€ 8.80 

-€ 8.80 

-€ 6.97 

-€ 8.87 

-€ 8.87 

-€ 8.87 

-€ 9.10 

-€ 9.40 

-€ 9.40 

-€ 9.40 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 3-12. 

Table 3-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

0.53 

-0.07 

-2.87 

0.53 

-0.07 

-2.87 

0.53 

-0.07 

-2.87 

0.53 

-0.07 

-2.87 

0.53 

-0.07 

-2.87 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

Mineral Waste and Asphalt 

Other C&D 

-1.87 

-0.51 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-1.87 

-0.51 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-1.87 

-0.51 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-1.87 

-0.51 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-1.87 

-0.51 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 3-13.   

Table 3-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and 
Asphalt 
Other C&D 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 36.24 

€ 127.54 

€ 134.05 

€ 147.91 

€ 209.62 

-€ 0.36 

-€ 0.90 

-€ 0.94 

-€ 1.01 

-€ 1.22 

-€ 66.39 

-€ 114.56 

-€ 120.40 

-€ 137.56 

-€ 229.50 

-€ 9.33 

-€ 27.10 

-€ 28.48 

-€ 35.38 

-€ 79.16 

€ 33.84 

-€ 110.45 

-€ 137.46 

-€ 175.74 

-€ 224.52 

-€ 0.07 

-€ 0.24 

-€ 0.25 

-€ 0.26 

-€ 0.31 

-€ 81.56 

-€ 153.12 

-€ 160.93 

-€ 184.39 

-€ 311.36 

€ 9.82 

-€ 1.26 

-€ 344.11 

-€ 518.76 

-€ 41.82 

€ 28.90 

€ 30.37 

-€ 3.60 
-€ 
1,023.36 
-€ 
1,416.02 
-€ 120.45 

-€ 3.78 
-€ 
1,075.56 
-€ 
1,488.25 
-€ 126.60 

€ 33.87 

-€ 4.15 

€ 50.61 

-€ 5.70 

-€ 1,139.69 

-€ 1,269.19 

-€ 1,576.98 

-€ 1,756.18 

-€ 134.14 

-€ 149.39 

-€ 984 

-€ 2,813 

-€ 2,978 

-€ 3,208 

-€ 3,766 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 3-14. 

28/05/2015 

9 

 
 
 
Table 3-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

0.60 

0.00 

-1.93 

-0.57 

0.28 

0.00 

-2.45 

0.20 

-0.02 

-0.94 

-1.42 

-0.11 

-6.35 

2.12 

-0.01 

-3.32 

-1.64 

-0.79 

0.00 

-4.60 

0.59 

-0.05 

-2.79 

-3.87 

-0.33 

2.23 

-0.01 

-3.49 

-1.73 

-0.83 

0.00 

-4.84 

0.62 

-0.05 

-2.94 

-4.06 

-0.35 

2.34 

-0.01 

-3.67 

-1.82 

-0.88 

0.00 

-5.08 

0.65 

-0.06 

-3.09 

-4.27 

-0.36 

2.46 

-0.01 

-3.86 

-1.91 

-0.92 

0.00 

-5.34 

0.68 

-0.06 

-3.24 

-4.49 

-0.38 

-14.70 

-15.45 

-16.24 

-17.07 

Note: Positive values denote an increase in greenhouse gas emissions. 

3.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 3-2 and Table 3-15. From this it 
is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

 
 
Figure 3-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

Table 3-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 0.98 

-€ 2.81 

-€ 2.98 

-€ 3.21 

-€ 3.77 

Financial Costs (social metric) 

-€ 0.82 

-€ 2.26 

-€ 2.38 

-€ 2.50 

-€ 2.63 

Net Costs and Benefits 

-€ 1.80 

-€ 5.08 

-€ 5.36 

-€ 5.71 

-€ 6.39 

-€ 37.1 

-€ 29.3 

-€ 66.4 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

11 

 
 
 
 
 
 
4.0  Croatia 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 4-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €9.3 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 4-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 8.5 

-€ 6.0 

-€ 14.5 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

 
 
                                                      
 
 
4.1 

Waste Generation and Management Projections 

4.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.7,8 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 4-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 4-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

267 

261 

286 

279 

300 

293 

315 

308 

332 

324 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
Croatia. We therefore proceeded to undertake a qualitative assessment of waste 
compositions in Croatia and judged that a ‘High Mineral Waste’ composition would be most 
appropriate (Table 4-3). 

Table 4-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

4.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 4-4 and Table 
4-5. 

7 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
8 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

13 

 
 
 
                                                      
 
Table 4-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

51.49% 

58.43% 

6.94% 

51.49% 

70.00% 

18.51% 

51.49% 

70.00% 

18.51% 

51.49% 

70.00% 

18.51% 

51.49% 

70.00% 

18.51% 

Table 4-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

4.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 4-6 and Table 4-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 4-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.01% 

0.01% 

0.00% 

0.01% 

0.01% 

0.00% 

0.01% 

0.01% 

0.00% 

0.01% 

0.01% 

0.00% 

0.01% 

0.01% 

0.00% 

Table 4-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

48.50% 

41.56% 

-6.94% 

48.50% 

29.99% 

-18.51% 

48.50% 

29.99% 

-18.51% 

48.50% 

29.99% 

-18.51% 

48.50% 

29.99% 

-18.51% 

4.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 4-8.  

Table 4-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

134 

144 

151 

159 

167 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

127 

135 

142 

149 

157 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

152 

195 

205 

216 

227 

0 

0 

108 

18 

0 

0 

-18 

0 

0 

84 

52 

0 

0 

-52 

0 

0 

88 

54 

0 

0 

-54 

0 

0 

92 

57 

0 

0 

-57 

0 

0 

97 

60 

0 

0 

-60 

Figure 4-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
offset by a decrease in landfill. 

Figure 4-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

4.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set 
Section 3 of Appendix 1. The calculated waste collection and treatment unit 
treatment type are summarised in  

Table 4-9. Note that these costs effectively include collection and sorting, and are quoted 
net of revenues generated from the sale of materials. 

28/05/2015 

15 

 
 
 
Table 4-9: Waste Collection and Treatment Unit Costs (2015 Real Term Prices), 
€ per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 29.51 

€ 29.51 

€ 29.01 

€ 28.01 

€ 34.34 

€ 19.37 

€ 3.32 

€ 31.21 

€ 28.89 

€ 21.28 

€ 21.40 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 4-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 4-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.03 

-€ 0.00 

-€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 2.34 

-€ 0.09 

-€ 1.76 

€ 0.07 

-€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.09 

-€ 0.00 

-€ 0.02 

€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.09 

-€ 0.00 

-€ 0.02 

€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.10 

-€ 0.00 

-€ 0.02 

€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.10 

-€ 0.00 

-€ 0.02 

€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 19.67 

€ 20.67 

€ 21.72 

€ 22.83 

-€ 0.24 

-€ 5.04 

€ 0.22 

-€ 0.02 

-€ 0.26 

-€ 5.29 

€ 0.23 

-€ 0.02 

-€ 0.27 

-€ 5.56 

€ 0.24 

-€ 0.03 

-€ 0.28 

-€ 5.85 

€ 0.25 

-€ 0.03 

-€ 71.11 

-€ 194.45 

-€ 204.37 

-€ 214.80 

-€ 225.75 

Mineral Waste and Asphalt 

-€ 92.47 

-€ 258.69 

-€ 271.89 

-€ 285.75 

-€ 300.33 

Other C&D 

-€ 8.59 

-€ 23.30 

-€ 24.49 

-€ 25.74 

-€ 27.06 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Total 

-€ 172 

-€ 462 

-€ 485 

-€ 510 

-€ 536 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

4.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 4-11. These costs reflect the combined impact of both the 
climate change impacts together with those impacts associated with other emissions to air 
such as NOx and PM. 

Table 4-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

€ 20.00 

€ 20.00 

€ 20.00 

€ 21.03 

€ 28.55 

-€ 14.03 

-€ 14.03 

-€ 14.03 

-€ 14.24 

-€ 15.79 

-€ 102.26 

-€ 102.26 

-€ 102.26 

-€ 110.87 

-€ 174.01 

-€ 64.55 

-€ 64.55 

-€ 64.55 

-€ 71.51 

-€ 122.58 

-€ 55.41 

-€ 64.54 

-€ 77.57 

-€ 95.71 

-€ 117.68 

-€ 5.69 

-€ 5.69 

-€ 5.69 

-€ 5.76 

-€ 6.29 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 65.44 

-€ 65.44 

-€ 65.44 

-€ 68.82 

-€ 93.64 

-€ 6.68 

-€ 9.27 

-€ 9.27 

-€ 9.27 

-€ 6.68 

-€ 9.27 

-€ 9.27 

-€ 9.27 

-€ 6.68 

-€ 9.27 

-€ 9.27 

-€ 9.27 

-€ 6.97 

-€ 9.34 

-€ 9.34 

-€ 9.34 

-€ 9.10 

-€ 9.87 

-€ 9.87 

-€ 9.87 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 4-12. 

Table 4-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

Plastics  

Switch from 

Wood 

28/05/2015 

0.34 

-0.07 

-2.87 

-2.32 

-0.51 

0.34 

-0.07 

-2.87 

-2.32 

-0.51 

0.34 

-0.07 

-2.87 

-2.32 

-0.51 

0.34 

-0.07 

-2.87 

-2.32 

-0.51 

0.34 

-0.07 

-2.87 

-2.32 

-0.51 

17 

 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Landfill to 
Recycling 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 4-13.   

Table 4-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.06 

-€ 0.00 

-€ 0.04 

-€ 0.05 

€ 0.00 

€ 0.20 

-€ 0.00 

-€ 0.09 

-€ 0.10 

€ 0.00 

€ 0.21 

-€ 0.00 

-€ 0.10 

-€ 0.10 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.24 

-€ 0.00 

-€ 0.11 

-€ 0.12 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.34 

-€ 0.00 

-€ 0.19 

-€ 0.22 

-€ 14.89 

-€ 145.54 

-€ 183.85 

-€ 238.41 

-€ 308.09 

-€ 0.04 

-€ 0.11 

-€ 0.11 

-€ 0.12 

-€ 0.14 

-€ 7.43 

-€ 21.20 

-€ 22.29 

-€ 25.54 

-€ 43.12 

-€ 1.35 

-€ 0.22 

-€ 3.91 

-€ 0.62 

-€ 4.11 

-€ 0.65 

-€ 4.54 

-€ 0.71 

-€ 6.49 

-€ 0.98 

-€ 67.16 

-€ 183.65 

-€ 193.01 

-€ 204.44 

-€ 227.02 

-€ 88.67 

-€ 248.05 

-€ 260.70 

-€ 276.13 

-€ 306.64 

-€ 8.24 

-€ 22.35 

-€ 23.49 

-€ 24.88 

-€ 27.62 

-€ 188 

-€ 625 

-€ 688 

-€ 775 

-€ 920 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 4-14. 

Table 4-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 

Wood 

Glass 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

 
 
 
 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.00 

0.00 

-0.14 

0.00 

-0.22 

-0.02 

0.00 

-0.17 

-0.23 

-0.02 

-0.81 

0.00 

0.00 

-1.14 

0.00 

-0.64 

-0.07 

-0.01 

-0.48 

-0.64 

-0.06 

-3.03 

0.00 

0.00 

-1.20 

0.00 

-0.67 

-0.07 

-0.01 

-0.50 

-0.68 

-0.06 

-3.19 

0.00 

0.00 

-1.26 

0.00 

-0.70 

-0.07 

-0.01 

-0.53 

-0.71 

-0.06 

-3.35 

0.00 

0.00 

-1.32 

0.00 

-0.74 

-0.08 

-0.01 

-0.55 

-0.75 

-0.07 

-3.52 

Note: Positive values denote an increase in greenhouse gas emissions. 

4.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 4-2 and Table 4-15. From this it 
is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

Figure 4-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

28/05/2015 

19 

 
 
 
 
Table 4-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 0.19 

-€ 0.63 

-€ 0.69 

-€ 0.77 

-€ 0.92 

Financial Costs (social metric) 

-€ 0.17 

-€ 0.46 

-€ 0.49 

-€ 0.51 

-€ 0.54 

Net Costs and Benefits 

-€ 0.36 

-€ 1.09 

-€ 1.17 

-€ 1.28 

-€ 1.46 

-€ 8.5 

-€ 6.0 

-€ 14.5 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

 
 
 
 
5.0  Cyprus 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 5-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €8.6 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 5-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 4.8 

-€ 3.8 

-€ 8.6 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

28/05/2015 

21 

 
 
                                                      
 
 
5.1 

Waste Generation and Management Projections 

5.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.9,10 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 5-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 5-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

137 

137 

146 

146 

154 

154 

162 

162 

170 

170 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
Cyprus. We therefore proceeded to undertake a qualitative assessment of waste 
compositions in Cyprus and judged that a ‘High Mineral Waste’ composition would be most 
appropriate (Table 5-3). 

Table 5-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.34% 

0.07% 

1.46% 

0.91% 

1.38% 

36.96% 

51.41% 

4.46% 

5.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 5-4 and Table 
5-5. 

9 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
10 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
Table 5-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

44.95% 

54.34% 

9.39% 

44.95% 

70.00% 

25.05% 

44.95% 

70.00% 

25.05% 

44.95% 

70.00% 

25.05% 

44.95% 

70.00% 

25.05% 

Table 5-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

15.40% 

12.52% 

-2.89% 

15.40% 

7.70% 

-7.70% 

15.40% 

7.70% 

-7.70% 

15.40% 

7.70% 

-7.70% 

15.40% 

7.70% 

-7.70% 

5.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 5-6 and Table 5-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 5-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

Table 5-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

39.65% 

33.14% 

-6.51% 

39.65% 

22.30% 

-17.35% 

39.65% 

22.30% 

-17.35% 

39.65% 

22.30% 

-17.35% 

39.65% 

22.30% 

-17.35% 

5.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 5-8.  

Table 5-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

28/05/2015 

Recycling 

Backfill 

Incineration 

Landfill 

62 

21 

0 

54 

66 

23 

0 

58 

69 

24 

0 

61 

76 

26 

0 

67 

73 

25 

0 

64 

23 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

74 

17 

0 

45 

13 

-4 

0 

-9 

103 

11 

0 

33 

37 

-11 

0 

-25 

108 

12 

0 

34 

39 

-12 

0 

-27 

113 

12 

0 

36 

41 

-12 

0 

-28 

119 

13 

0 

38 

43 

-13 

0 

-30 

Figure 5-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
mostly offset by a decrease in landfill, as well as a significant reduction in backfilling. 

Figure 5-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

5.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 5-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

 
 
 
Table 5-9: Waste Collection and Treatment Unit Costs (2015 Real Term Prices), 
€ per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 31.39 

€ 31.39 

€ 30.89 

€ 29.89 

€ 37.69 

€ 20.59 

€ 6.94 

€ 33.72 

€ 30.90 

€ 22.72 

€ 22.85 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 5-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 5-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

2015 

-€ 12.87 

-€ 17.62 

-€ 1.53 

2020 

-€ 36.69 

-€ 50.24 

-€ 4.36 

2025 

-€ 38.56 

-€ 52.80 

-€ 4.58 

2030 

2035 

-€ 40.53 

-€ 42.60 

-€ 55.49 

-€ 58.32 

-€ 4.82 

-€ 5.06 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.85 

-€ 0.05 

-€ 1.38 

€ 0.04 

-€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 8.01 

-€ 0.15 

-€ 3.94 

€ 0.10 

-€ 0.03 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 8.41 

-€ 0.15 

-€ 4.14 

€ 0.11 

-€ 0.03 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 8.84 

-€ 0.16 

-€ 4.35 

€ 0.11 

-€ 0.04 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 9.29 

-€ 0.17 

-€ 4.57 

€ 0.12 

-€ 0.04 

-€ 29.98 

-€ 83.39 

-€ 87.64 

-€ 92.11 

-€ 96.81 

Mineral Waste and Asphalt 

-€ 41.06 

-€ 111.70 

-€ 117.39 

-€ 123.38 

-€ 129.68 

Other C&D 

Total 

-€ 3.51 

-€ 107 

-€ 9.91 

-€ 292 

-€ 10.42 

-€ 10.95 

-€ 11.51 

-€ 307 

-€ 323 

-€ 339 

28/05/2015 

25 

 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

5.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 5-11. These costs reflect the combined impact of both the 
climate change impacts together with those impacts associated with other emissions to air 
such as NOx and PM. 

Table 5-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 24.97 

-€ 4.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 24.97 

-€ 4.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 24.97 

-€ 4.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 26.42 

-€ 4.82 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 37.07 

-€ 6.65 

-€ 93.99 

-€ 93.99 

-€ 93.99 

-€ 102.64 

-€ 166.06 

-€ 41.30 

-€ 41.30 

-€ 41.30 

-€ 47.21 

-€ 90.57 

-€ 74.72 

-€ 83.46 

-€ 95.93 

-€ 113.31 

-€ 134.40 

-€ 4.50 

-€ 4.50 

-€ 4.50 

-€ 4.57 

-€ 5.10 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 42.52 

-€ 42.52 

-€ 42.52 

-€ 45.91 

-€ 70.73 

-€ 6.68 

-€ 8.08 

-€ 8.08 

-€ 8.08 

-€ 6.68 

-€ 8.08 

-€ 8.08 

-€ 8.08 

-€ 6.68 

-€ 8.08 

-€ 8.08 

-€ 8.08 

-€ 6.97 

-€ 8.15 

-€ 8.15 

-€ 8.15 

-€ 9.10 

-€ 8.68 

-€ 8.68 

-€ 8.68 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 5-12. 

Table 5-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

Plastics  

0.48 

-0.08 

-2.88 

-1.97 

0.48 

-0.08 

-2.88 

-1.97 

0.48 

-0.08 

-2.88 

-1.97 

0.48 

-0.08 

-2.88 

-1.97 

0.48 

-0.08 

-2.88 

-1.97 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

Mineral Waste and Asphalt 

Other C&D 

-0.49 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-0.49 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-0.49 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-0.49 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-0.49 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 5-13.   

Table 5-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

-€ 5.63 

-€ 16.05 

-€ 16.87 

-€ 17.73 

-€ 18.64 

-€ 7.83 

-€ 22.33 

-€ 23.46 

-€ 24.66 

-€ 25.92 

-€ 0.68 

-€ 1.94 

-€ 2.04 

-€ 2.14 

-€ 2.25 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 10.12 

-€ 106.09 

-€ 128.17 

-€ 159.10 

-€ 198.35 

-€ 0.02 

-€ 0.06 

-€ 0.06 

-€ 0.07 

-€ 0.08 

-€ 5.30 

-€ 15.12 

-€ 15.90 

-€ 18.21 

-€ 30.75 

-€ 0.65 

-€ 0.15 

-€ 1.85 

-€ 0.44 

-€ 1.94 

-€ 0.46 

-€ 2.21 

-€ 0.51 

-€ 3.57 

-€ 0.70 

-€ 27.95 

-€ 77.74 

-€ 81.71 

-€ 86.64 

-€ 96.96 

-€ 38.85 

-€ 105.68 

-€ 111.07 

-€ 117.78 

-€ 131.81 

-€ 3.32 

-€ 101 

-€ 9.38 

-€ 357 

-€ 9.86 

-€ 392 

-€ 10.45 

-€ 11.70 

-€ 440 

-€ 521 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 5-14. 

Table 5-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 

Wood 

0.00 

0.00 

0.00 

0.00 

0.00 

28/05/2015 

27 

 
 
 
 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.00 

0.00 

0.00 

-0.07 

0.00 

-0.16 

-0.02 

0.00 

-0.08 

-0.12 

-0.01 

-0.45 

0.00 

0.00 

0.00 

-0.62 

0.00 

-0.45 

-0.05 

-0.01 

-0.23 

-0.31 

-0.03 

-1.70 

0.00 

0.00 

0.00 

-0.65 

0.00 

-0.48 

-0.05 

-0.01 

-0.24 

-0.33 

-0.03 

-1.79 

0.00 

0.00 

0.00 

-0.68 

0.00 

-0.50 

-0.05 

-0.01 

-0.26 

-0.35 

-0.03 

-1.88 

0.00 

0.00 

0.00 

-0.72 

0.00 

-0.53 

-0.06 

-0.01 

-0.27 

-0.36 

-0.03 

-1.98 

Note: Positive values denote an increase in greenhouse gas emissions. 

5.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 5-2 and Table 5-15. From this it 
is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

Figure 5-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

 
 
 
 
Table 5-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 0.10 

-€ 0.36 

-€ 0.39 

-€ 0.44 

-€ 0.52 

Financial Costs (social metric) 

-€ 0.11 

-€ 0.29 

-€ 0.31 

-€ 0.32 

-€ 0.34 

Net Costs and Benefits 

-€ 0.21 

-€ 0.65 

-€ 0.70 

-€ 0.76 

-€ 0.86 

-€ 4.8 

-€ 3.8 

-€ 8.6 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

29 

 
 
 
 
6.0  Czech Republic 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 6-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €74 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 6-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 51.8 

-€ 31.8 

-€ 83.6 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

 
 
                                                      
 
 
6.1 

Waste Generation and Management Projections 

6.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.11,12 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 6-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 6-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

2,946 

3,430 

3,150 

3,668 

3,311 

3,855 

3,479 

4,052 

3,657 

4,258 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1). 

The C&D waste composition for the Czech Republic reported in the literature is most similar 
to the ‘High Mineral Waste’ composition, and therefore this compositional set was used for 
modelling (Table 6-3).13 

Table 6-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

6.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 6-4 and Table 
6-5. 

11 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
12 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 
13 European Commission - Joint Research Centre (2008) End of Waste Criteria, 
http://susproc.jrc.ec.europa.eu/documents/Endofwastecriteriafinal.pdf 

28/05/2015 

31 

 
 
 
                                                      
 
Table 6-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

60.23% 

63.89% 

3.66% 

60.23% 

70.00% 

9.77% 

60.23% 

70.00% 

9.77% 

60.23% 

70.00% 

9.77% 

60.23% 

70.00% 

9.77% 

Table 6-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

30.82% 

27.15% 

-3.66% 

30.82% 

21.05% 

-9.77% 

30.82% 

21.05% 

-9.77% 

30.82% 

21.05% 

-9.77% 

30.82% 

21.05% 

-9.77% 

6.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 6-6 and Table 6-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 6-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.10% 

0.10% 

0.00% 

0.10% 

0.10% 

0.00% 

0.10% 

0.10% 

0.00% 

0.10% 

0.10% 

0.00% 

0.10% 

0.10% 

0.00% 

Table 6-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

8.85% 

8.85% 

0.00% 

8.85% 

8.85% 

0.00% 

8.85% 

8.85% 

0.00% 

8.85% 

8.85% 

0.00% 

8.85% 

8.85% 

0.00% 

6.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 6-8.  

Table 6-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

2,066 

1,057 

3 

304 

2,209 

1,130 

4 

325 

2,322 

1,188 

4 

341 

2,440 

1,249 

4 

359 

2,565 

1,312 

4 

377 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

2,192 

2,568 

2,698 

2,836 

2,981 

931 

3 

304 

126 

-126 

0 

0 

772 

4 

325 

358 

-358 

0 

0 

811 

4 

341 

377 

-377 

0 

0 

853 

4 

359 

396 

-396 

0 

0 

896 

4 

377 

416 

-416 

0 

0 

Figure 6-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
offset by a decrease in backfilling. 

Figure 6-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

6.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 6-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

28/05/2015 

33 

 
 
 
Table 6-9: Waste Collection and Treatment Unit Costs (2015 Real Term Prices), 
€ per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 29.87 

€ 29.87 

€ 29.37 

€ 28.37 

€ 34.92 

€ 19.59 

€ 3.91 

€ 31.67 

€ 29.27 

€ 21.55 

€ 21.67 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 6-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 6-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Soil 

-€ 390.98 

Mineral Waste and Asphalt 

-€ 535.40 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Incineration 
to Recycling 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

-€ 
1,114.90 
-€ 
1,526.72 
-€ 132.53 

-€ 
1,171.77 
-€ 
1,604.60 
-€ 139.29 

-€ 
1,231.54 
-€ 
1,686.45 
-€ 146.40 

-€ 
1,294.36 
-€ 
1,772.48 
-€ 153.86 

€ 0.83 

€ 0.06 

-€ 0.15 

-€ 0.30 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.87 

€ 0.06 

-€ 0.16 

-€ 0.31 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.92 

€ 0.07 

-€ 0.17 

-€ 0.33 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.96 

€ 0.07 

-€ 0.18 

-€ 0.34 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 46.48 

€ 0.25 

€ 0.02 

-€ 0.05 

-€ 0.09 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 43.23 

€ 123.18 

€ 129.47 

€ 136.07 

€ 143.01 

-€ 0.50 

-€ 1.42 

-€ 1.50 

-€ 1.57 

-€ 1.65 

-€ 14.27 

-€ 40.66 

-€ 42.74 

-€ 44.92 

-€ 47.21 

€ 0.36 

-€ 0.13 

€ 1.06 

-€ 0.38 

€ 1.12 

-€ 0.40 

€ 1.17 

-€ 0.42 

€ 1.23 

-€ 0.44 

€ 29.81 

€ 85.01 

€ 89.35 

€ 93.90 

€ 98.69 

Mineral Waste and Asphalt 

€ 45.47 

€ 129.67 

€ 136.28 

€ 143.23 

€ 150.54 

Other C&D 

€ 3.55 

€ 10.11 

€ 10.63 

€ 11.17 

€ 11.74 

 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Total 

-€ 865 

-€ 2,467 

-€ 2,593 

-€ 2,725 

-€ 2,864 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

6.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 6-11. These costs reflect the combined impact of both the 
climate change impacts together with those impacts associated with other emissions to air 
such as NOx and PM. 

Table 6-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

€ 33.00 

€ 33.00 

€ 33.00 

€ 34.13 

€ 42.39 

-€ 15.06 

-€ 15.06 

-€ 15.06 

-€ 15.28 

-€ 16.90 

-€ 103.33 

-€ 103.33 

-€ 103.33 

-€ 111.95 

-€ 175.15 

-€ 32.04 

-€ 32.04 

-€ 32.04 

-€ 38.75 

-€ 88.01 

-€ 80.88 

-€ 93.15 

-€ 110.66 

-€ 135.10 

-€ 165.08 

-€ 5.65 

-€ 5.65 

-€ 5.65 

-€ 5.72 

-€ 6.25 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 64.85 

-€ 64.85 

-€ 64.85 

-€ 68.23 

-€ 93.05 

-€ 6.68 

-€ 9.23 

-€ 9.23 

-€ 9.23 

-€ 6.68 

-€ 9.23 

-€ 9.23 

-€ 9.23 

-€ 6.68 

-€ 9.23 

-€ 9.23 

-€ 9.23 

-€ 6.97 

-€ 9.30 

-€ 9.30 

-€ 9.30 

-€ 9.10 

-€ 9.83 

-€ 9.83 

-€ 9.83 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 6-12. 

Table 6-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

0.38 

-0.07 

-2.87 

0.38 

-0.07 

-2.87 

0.38 

-0.07 

-2.87 

0.38 

-0.07 

-2.87 

0.38 

-0.07 

-2.87 

28/05/2015 

35 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

Mineral Waste and Asphalt 

Other C&D 

-2.24 

-1.20 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.24 

-1.20 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.24 

-1.20 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.24 

-1.20 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.24 

-1.20 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 6-13.   

Table 6-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

-€ 178.85 

-€ 509.99 

-€ 536.00 

-€ 563.35 

-€ 592.08 

-€ 248.73 

-€ 709.28 

-€ 745.46 

-€ 783.48 

-€ 823.45 

-€ 21.59 

-€ 61.57 

-€ 64.71 

-€ 68.01 

-€ 71.48 

€ 1.66 

€ 0.03 

-€ 0.19 

€ 1.61 

-€ 691.22 

-€ 0.27 

€ 5.41 

€ 0.09 

€ 5.69 

€ 0.10 

-€ 0.61 

-€ 0.64 

€ 5.25 
-€ 
2,268.23 
-€ 0.78 

€ 5.52 
-€ 
2,832.10 
-€ 0.82 

€ 6.18 

€ 0.10 

-€ 0.73 

€ 7.02 

€ 8.07 

€ 0.12 

-€ 1.20 

€ 16.75 

-€ 3,633.99 

-€ 4,666.83 

-€ 0.88 

-€ 1.01 

-€ 51.63 

-€ 147.16 

-€ 154.67 

-€ 177.22 

-€ 299.25 

-€ 12.93 

-€ 38.19 

-€ 40.14 

-€ 44.39 

-€ 63.62 

-€ 1.51 

-€ 4.30 

-€ 4.51 

-€ 4.95 

-€ 6.80 

€ 33.11 

€ 94.41 

€ 99.23 

€ 105.10 

€ 116.74 

€ 51.24 

€ 146.12 

€ 153.57 

€ 162.66 

€ 180.67 

€ 4.00 

€ 11.40 

€ 11.98 

€ 12.69 

€ 14.09 

-€ 1,115 

-€ 3,477 

-€ 4,103 

-€ 4,983 

-€ 6,189 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 6-14. 

 
 
 
Table 6-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.02 

0.00 

-0.01 

0.11 

0.06 

0.00 

-0.02 

0.37 

0.06 

0.00 

-0.02 

0.39 

0.07 

0.00 

-0.02 

0.41 

0.07 

0.00 

-0.02 

0.43 

-10.30 

-29.33 

-30.83 

-32.40 

-34.05 

0.00 

-1.55 

-0.22 

-0.02 

0.09 

0.13 

0.01 

0.00 

-4.42 

-0.66 

-0.06 

0.25 

0.38 

0.03 

0.00 

-4.65 

-0.70 

-0.07 

0.26 

0.40 

0.03 

0.00 

-4.89 

-0.73 

-0.07 

0.27 

0.42 

0.03 

0.00 

-5.14 

-0.77 

-0.07 

0.29 

0.44 

0.03 

Total 

-11.74 

-33.42 

-35.12 

-36.92 

-38.80 

Note: Positive values denote an increase in greenhouse gas emissions. 

6.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 6-2 and Table 6-15. From this it 
is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

28/05/2015 

37 

 
 
Figure 6-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

Table 6-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 1.12 

-€ 3.48 

-€ 4.10 

-€ 4.98 

-€ 6.19 

Financial Costs (social metric) 

-€ 0.87 

-€ 2.47 

-€ 2.59 

-€ 2.73 

-€ 2.86 

Net Costs and Benefits 

-€ 1.98 

-€ 5.94 

-€ 6.70 

-€ 7.71 

-€ 9.05 

-€ 51.8 

-€ 31.8 

-€ 83.6 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

 
 
 
 
 
 
7.0  Denmark 

According to Eurostat, the C&D recycling rate for Denmark was 87% in 2012.14,15 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

14 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
15 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

39 

 
 
 
                                                      
 
8.0  Estonia 

According to Eurostat, the C&D recycling rate for Estonia was 75% in 2012.16,17 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

16 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
17 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
 
                                                      
 
9.0  Finland 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 9-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €2,287 million, in 2015 real term prices, over the period from 
2015 to 2035 in net present value terms. 

Table 9-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 1,057 

-€ 227 

-€ 1,285 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

28/05/2015 

41 

 
 
                                                      
 
 
9.1 

Waste Generation and Management Projections 

9.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.18,19 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 9-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 9-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

16,318 

4,503 

17,150 

4,732 

18,025 

4,974 

18,944 

5,227 

19,910 

5,494 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

The C&D waste composition for Finland reported in the literature is most similar to the ‘High 
Wood’ composition, and therefore this compositional set was used for modelling (Table 
9-3).20 

Table 9-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Wood 

26.0% 

0.1% 

9.4% 

1.5% 

2.3% 

30.6% 

24.1% 

6.0% 

9.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 9-4 and Table 
9-5. 

18 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
19 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 
20 VTT Technical Research Centre of Finland (2006) Expert Study to Support Building Waste Statistics of the Year 
2004 

 
 
 
                                                      
 
Table 9-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

11.79% 

33.62% 

21.83% 

11.79% 

70.00% 

58.21% 

11.79% 

70.00% 

58.21% 

11.79% 

70.00% 

58.21% 

11.79% 

70.00% 

58.21% 

Table 9-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

9.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 9-6 and Table 9-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 9-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

4.49% 

3.38% 

-1.11% 

4.49% 

1.53% 

-2.96% 

4.49% 

1.53% 

-2.96% 

4.49% 

1.53% 

-2.96% 

4.49% 

1.53% 

-2.96% 

Table 9-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

83.72% 

63.00% 

-20.72% 

83.72% 

28.47% 

-55.25% 

83.72% 

28.47% 

-55.25% 

83.72% 

28.47% 

-55.25% 

83.72% 

28.47% 

-55.25% 

9.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 9-8.  

Table 9-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

531 

0 

202 

558 

0 

212 

587 

0 

223 

616 

0 

235 

648 

0 

247 

3,770 

3,962 

4,164 

4,376 

4,600 

28/05/2015 

43 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

1,514 

3,313 

3,482 

3,659 

3,846 

0 

152 

2,837 

983 

0 

-50 

-933 

0 

72 

1,347 

2,755 

0 

-140 

-2,614 

0 

76 

1,416 

2,895 

0 

-147 

-2,748 

0 

80 

1,488 

3,043 

0 

-155 

-2,888 

0 

84 

1,564 

3,198 

0 

-163 

-3,035 

Figure 9-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
mostly offset by a decrease in landfill, as well as a reduction in incineration. 

Figure 9-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

9.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 9-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

 
 
 
 
Table 9-9: Waste Collection and Treatment Unit Costs (2015 Real Term Prices), 
€ per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 39.36 

€ 39.36 

€ 38.86 

€ 37.86 

€ 50.07 

€ 25.38 

€ 19.22 

€ 43.91 

€ 39.29 

€ 28.83 

€ 28.99 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 9-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 9-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

Mineral Waste and Asphalt 

€ 0 

€ 0 

€ 0 

€ 211 

-€ 1 

-€ 427 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 691 

-€ 4 

-€ 767 

€ 6 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 726 

-€ 4 

-€ 806 

€ 6 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 763 

-€ 5 

-€ 847 

€ 7 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 802 

-€ 5 

-€ 890 

€ 7 

€ 0 

€ 0 

€ 0 

€ 0 

€ 1,352 

€ 3,583 

€ 3,766 

€ 3,958 

€ 4,160 

-€ 7 

-€ 19 

-€ 20 

-€ 21 

-€ 22 

-€ 2,533 

-€ 4,249 

-€ 4,466 

-€ 4,694 

-€ 4,933 

€ 5 

-€ 1 

€ 13 

-€ 4 

€ 13 

-€ 4 

€ 14 

-€ 4 

€ 15 

-€ 4 

-€ 2,733 

-€ 2,223 

-€ 8,440 

-€ 6,666 

-€ 8,871 

-€ 7,006 

-€ 9,324 

-€ 7,364 

-€ 9,799 

-€ 7,739 

Other C&D 

-€ 520 

-€ 1,558 

-€ 1,637 

-€ 1,721 

-€ 1,809 

Total 

-€ 6,878 

-€ 17,415 

-€ 18,303 

-€ 19,237 

-€ 20,218 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

45 

 
9.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 9-11. These costs reflect the combined impact of both the 
climate change impacts together with those impacts associated with other emissions to air 
such as NOx and PM. 

Table 9-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 55.98 

-€ 6.26 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 55.98 

-€ 6.26 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 55.98 

-€ 6.26 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 59.04 

-€ 6.56 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 81.48 

-€ 8.75 

-€ 95.59 

-€ 95.59 

-€ 95.59 

-€ 104.28 

-€ 168.06 

€ 31.27 

€ 31.27 

€ 31.27 

€ 29.19 

€ 13.97 

-€ 66.19 

-€ 74.99 

-€ 87.54 

-€ 105.12 

-€ 126.99 

-€ 4.59 

-€ 4.59 

-€ 4.59 

-€ 4.66 

-€ 5.19 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 44.85 

-€ 44.85 

-€ 44.85 

-€ 48.23 

-€ 73.05 

-€ 6.68 

-€ 8.17 

-€ 8.17 

-€ 8.17 

-€ 6.68 

-€ 8.17 

-€ 8.17 

-€ 8.17 

-€ 6.68 

-€ 8.17 

-€ 8.17 

-€ 8.17 

-€ 6.97 

-€ 8.24 

-€ 8.24 

-€ 8.24 

-€ 9.10 

-€ 8.77 

-€ 8.77 

-€ 8.77 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 9-12. 

Table 9-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

1.02 

-0.10 

-2.90 

-0.69 

-0.47 

-0.02 

-2.82 

-1.13 

1.02 

-0.10 

-2.90 

-0.69 

-0.47 

-0.02 

-2.82 

-1.13 

1.02 

-0.10 

-2.90 

-0.69 

-0.47 

-0.02 

-2.82 

-1.13 

1.02 

-0.10 

-2.90 

-0.69 

-0.47 

-0.02 

-2.82 

-1.13 

1.02 

-0.10 

-2.90 

-0.69 

-0.47 

-0.02 

-2.82 

-1.13 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 9-13.   

Table 9-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 1,821 

€ 5,952 

€ 6,256 

€ 6,934 

€ 10,059 

-€ 0.59 

-€ 2.31 

-€ 2.42 

-€ 2.67 

-€ 3.74 

-€ 1,659 

-€ 2,9785 

-€ 3,130 

-€ 3,5893 

-€ 6,079 

€ 1.17 

€ 72 

€ 76.38 

€ 74.95 

€ 37.69 

-€ 13,774 

-€ 41,360 

-€ 50,748 

-€ 64,045 

-€ 81,317 

-€ 3.02 

-€ 7.60 

-€ 7.99 

-€ 8.53 

-€ 9.98 

-€ 9,668 

-€ 16,217 

-€ 17,044 

-€ 19,529 

-€ 32,977 

-€ 84 

-€ 19 

-€ 223 

-€ 54 

-€ 234 

-€ 57 

-€ 265 

-€ 62 

-€ 422 

-€ 86 

-€ 2,494 

-€ 7,705 

-€ 8,098 

-€ 8,586 

-€ 9,603 

-€ 2,059 

-€ 6,176 

-€ 6,4916 

-€ 6,883 

-€ 7,698 

-€ 481 

-€ 1,443 

-€ 1,517 

-€ 1,608 

-€ 1,799 

-€ 28,424 

-€ 70,144 

-€ 81,001 

-€ 97,573 

-€ 129,901 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 9-14. 

Table 9-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

Plastics  

33.19 

-0.01 

-50.32 

-0.03 

108.48 

114.01 

119.83 

125.94 

-0.04 

-90.33 

-1.61 

-0.04 

-94.94 

-1.69 

-0.04 

-0.04 

-99.79 

-104.88 

-1.78 

-1.87 

Switch from 

Wood 

-96.92 

-256.88 

-269.98 

-283.76 

-298.23 

28/05/2015 

47 

 
 
 
 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Landfill to 
Recycling 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-0.02 

-0.04 

-0.04 

-0.04 

-0.05 

-290.65 

-487.51 

-512.38 

-538.52 

-565.99 

-2.12 

-0.28 

-7.34 

-6.06 

-1.42 

-5.62 

-0.79 

-22.65 

-18.16 

-4.24 

-5.90 

-0.83 

-23.81 

-19.09 

-4.46 

-6.20 

-0.87 

-25.02 

-20.06 

-4.69 

-6.52 

-0.92 

-26.30 

-21.08 

-4.93 

Total 

-421.97 

-779.40 

-819.16 

-860.94 

-904.86 

Note: Positive values denote an increase in greenhouse gas emissions. 

9.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 9-2 and Table 9-15. From this it 
is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

Figure 9-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

 
 
 
 
Table 9-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

-€ 28 

-€ 7 

-€ 35 

-€ 70 

-€ 17 

-€ 88 

-€ 81 

-€ 18 

-€ 98 

-€ 19 

-€ 99 

-€ 117 

-€ 130 

-€ 20 

-€ 150 

-€ 1,057 

-€ 227 

-€ 1,285 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

49 

 
 
 
 
10.0  France 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 10-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €3,697 million, in 2015 real term prices, over the period from 
2015 to 2035 in net present value terms. 

Table 10-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 1,346 

-€ 724 

-€ 2,070 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

 
 
                                                      
 
 
10.1  Waste Generation and Management Projections 

10.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.21,22 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 10-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 10-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

63,345 

62,969 

66,576 

66,181 

69,972 

69,557 

73,542 

73,105 

77,293 

76,834 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
France. We therefore proceeded to undertake a qualitative assessment of waste 
compositions in France and judged that a ‘High Mineral Waste’ composition would be most 
appropriate (Table 10-3). 

Table 10-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

10.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 10-4 and Table 
10-5. 

21 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
22 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

51 

 
 
 
                                                      
 
Table 10-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

58.70% 

62.94% 

4.24% 

58.70% 

70.00% 

11.30% 

58.70% 

70.00% 

11.30% 

58.70% 

70.00% 

11.30% 

58.70% 

70.00% 

11.30% 

Table 10-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

7.54% 

6.13% 

-1.41% 

7.54% 

3.77% 

-3.77% 

7.54% 

3.77% 

-3.77% 

7.54% 

3.77% 

-3.77% 

7.54% 

3.77% 

-3.77% 

10.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 10-6 and Table 10-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 10-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.05% 

0.04% 

0.00% 

0.05% 

0.04% 

-0.01% 

0.05% 

0.04% 

-0.01% 

0.05% 

0.04% 

-0.01% 

0.05% 

0.04% 

-0.01% 

Table 10-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

33.71% 

30.89% 

-2.82% 

33.71% 

26.19% 

-7.52% 

33.71% 

26.19% 

-7.52% 

33.71% 

26.19% 

-7.52% 

33.71% 

26.19% 

-7.52% 

10.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 10-8.  

Table 10-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

36,962 

38,847 

40,829 

42,911 

45,100 

4,748 

4,991 

5,245 

5,513 

5,794 

30 

32 

33 

35 

37 

21,228 

22,311 

23,449 

24,646 

25,903 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

39,630 

46,326 

48,690 

51,173 

53,784 

3,858 

2,495 

2,623 

2,756 

2,897 

27 

24 

26 

27 

28 

19,453 

17,334 

18,219 

19,148 

20,125 

2,669 

-890 

-3 

7,479 

-2,495 

-7 

7,861 

-2,623 

-7 

8,262 

-2,756 

-8 

8,683 

-2,897 

-8 

-1,776 

-4,977 

-5,231 

-5,498 

-5,778 

Figure 10-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
mostly offset by a decrease in landfill, as well as a significant reduction in backfilling. 

Figure 10-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

10.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 10-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

28/05/2015 

53 

 
 
 
 
Table 10-9: Waste Collection and Treatment Unit Costs (2015 Real Term 
Prices), € per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 37.69 

€ 37.69 

€ 37.19 

€ 36.19 

€ 47.57 

€ 24.40 

€ 16.80 

€ 41.80 

€ 37.55 

€ 27.55 

€ 27.71 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 10-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 10-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Soil 

-€ 2,848 

-€ 7,982 

-€ 8,389 

-€ 8,817 

-€ 9,267 

Mineral Waste and Asphalt 

-€ 3,900 

-€ 10,929 

-€ 11,487 

-€ 12,073 

-€ 12,688 

Other C&D 

-€ 339 

-€ 949 

-€ 997 

-€ 1,048 

-€ 1,101 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Incineration 
to Recycling 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

€ 11 

€ 0 

-€ 5 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 729 

-€ 10 

-€ 298 

€ 6 

-€ 3 

€ 33 

€ 0 

-€ 11 

€ 1 

€ 0 

€ 0 

€ 0 

€ 0 

€ 35 

-€ 1 

-€ 12 

€ 1 

€ 0 

€ 0 

€ 0 

€ 0 

€ 37 

-€ 1 

-€ 13 

€ 1 

€ 0 

€ 0 

€ 0 

€ 0 

€ 38 

-€ 1 

-€ 13 

€ 1 

€ 0 

€ 0 

€ 0 

€ 0 

€ 2,450 

€ 2,575 

€ 2,707 

€ 2,845 

-€ 29 

-€ 838 

€ 17 

-€ 8 

-€ 31 

-€ 881 

€ 18 

-€ 8 

-€ 32 

-€ 925 

€ 19 

-€ 8 

-€ 34 

-€ 973 

€ 20 

-€ 9 

-€ 5,605 

-€ 15,336 

-€ 16,119 

-€ 16,941 

-€ 17,805 

Mineral Waste and Asphalt 

-€ 7,418 

-€ 20,566 

-€ 21,615 

-€ 22,717 

-€ 23,876 

Other C&D 

-€ 672 

-€ 1,830 

-€ 1,924 

-€ 2,022 

-€ 2,125 

Total 

-€ 20,350 

-€ 55,977 

-€ 58,832 

-€ 61,833 

-€ 64,987 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

 
10.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 10-11. These costs reflect the combined impact of both 
the climate change impacts together with those impacts associated with other emissions to 
air such as NOx and PM. 

Table 10-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 5.48 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 5.48 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 5.48 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 5.50 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 5.64 

-€ 13.62 

-€ 13.62 

-€ 13.62 

-€ 13.74 

-€ 14.62 

-€ 101.61 

-€ 101.61 

-€ 101.61 

-€ 110.13 

-€ 172.59 

-€ 131.74 

-€ 131.74 

-€ 131.74 

-€ 141.27 

-€ 211.22 

-€ 80.61 

-€ 89.49 

-€ 102.59 

-€ 121.51 

-€ 144.96 

-€ 5.93 

-€ 5.93 

-€ 5.93 

-€ 6.00 

-€ 6.53 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 72.14 

-€ 72.14 

-€ 72.14 

-€ 75.52 

-€ 100.34 

-€ 6.68 

-€ 9.51 

-€ 9.51 

-€ 9.51 

-€ 6.68 

-€ 9.51 

-€ 9.51 

-€ 9.51 

-€ 6.68 

-€ 9.51 

-€ 9.51 

-€ 9.51 

-€ 6.97 

-€ 9.58 

-€ 9.58 

-€ 9.58 

-€ 9.10 

-€ 10.11 

-€ 10.11 

-€ 10.11 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 10-12. 

Table 10-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

28/05/2015 

-0.01 

-0.04 

-2.84 

-3.18 

-0.55 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.01 

-0.04 

-2.84 

-3.18 

-0.55 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.01 

-0.04 

-2.84 

-3.18 

-0.55 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.01 

-0.04 

-2.84 

-3.18 

-0.55 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.01 

-0.04 

-2.84 

-3.18 

-0.55 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

55 

 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Mineral Waste and Asphalt 

Other C&D 

-0.02 

-0.02 

-0.02 

-0.02 

-0.02 

-0.02 

-0.02 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 10-13.   

Table 10-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

-€1,267 

-€3,551 

-€3,732 

-€3,922 

-€4,122 

-€1,762 

-€4,938 

-€5,190 

-€5,455 

-€5,733 

-€153 

-€12 

€0 

-€18 

-€24 

-€429 

-€451 

-€474 

-€498 

-€34 

-€1 

-€45 

-€45 

-€36 

-€1 

-€47 

-€47 

-€38 

-€1 

-€53 

-€54 

-€41 

-€1 

-€88 

-€84 

-€11,016 

-€41,111 

-€49,536 

-€61,661 

-€77,313 

-€6 

-€16 

-€17 

-€18 

-€21 

-€1,084 

-€3,042 

-€3,197 

-€3,663 

-€6,185 

-€215 

-€32 

-€615 

-€90 

-€646 

-€94 

-€711 

-€103 

-€993 

-€142 

-€6,247 

-€17,093 

-€17,965 

-€19,025 

-€21,098 

-€8,390 

-€23,260 

-€24,447 

-€25,889 

-€28,710 

-€760 

-€2,070 

-€ 30,985 

-€ 96,340 

-€2,176 
-€ 
107,582 

-€2,304 

-€2,555 

-€ 123,370 

-€ 147,584 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 10-14. 

Table 10-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

-0.01 

0.00 

-0.49 

-0.59 

-0.04 

0.00 

-1.25 

-1.09 

-0.04 

0.00 

-1.31 

-1.15 

-0.04 

0.00 

-1.38 

-1.20 

-0.05 

0.00 

-1.45 

-1.27 

-75.32 

-253.21 

-266.13 

-279.71 

-293.97 

-0.02 

-0.07 

-0.07 

-0.07 

-0.08 

 
 
 
 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Recycling 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-32.57 

-91.43 

-3.36 

-0.46 

-15.78 

-21.19 

-1.92 

-9.62 

-1.30 

-43.18 

-58.76 

-5.23 

-96.09 

-10.11 

-1.37 

-45.38 

-61.76 

-5.50 

-101.00 

-106.15 

-10.63 

-1.44 

-47.70 

-64.91 

-5.78 

-11.17 

-1.51 

-50.13 

-68.22 

-6.07 

Total 

-151.74 

-465.18 

-488.91 

-513.85 

-540.06 

Note: Positive values denote an increase in greenhouse gas emissions. 

10.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 10-2 and Table 10-15. From this 
it is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

Figure 10-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

w

28/05/2015 

57 

 
 
 
 
Table 10-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

Financial Costs (social metric) 

-€ 31 

-€ 20 

-€ 96 

-€ 56 

-€ 108 

-€ 123 

-€ 148 

-€ 59 

-€ 62 

-€ 65 

Net Costs and Benefits 

-€ 51 

-€ 152 

-€ 166 

-€ 185 

-€ 213 

-€ 1,346 

-€ 724 

-€ 2,070 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

 
 
 
 
11.0  Germany 

According to Eurostat, the C&D recycling rate for Germany was 85% in 2012.23,24 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

23 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
24 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

59 

 
 
 
                                                      
 
12.0  Greece 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 12-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €135 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 12-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 70.0 

-€ 64.8 

-€ 134.9 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

 
 
                                                      
 
 
12.1  Waste Generation and Management Projections 

12.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.25,26 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 12-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 12-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

632 

632 

676 

675 

710 

710 

746 

746 

785 

784 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
Greece We therefore proceeded to undertake a qualitative assessment of waste 
compositions in Greece and judged that a ‘High Mineral Waste’ composition would be most 
appropriate (Table 12-3). 

Table 12-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

12.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 12-4 and Table 
12-5. 

25 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
26 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

61 

 
 
 
                                                      
 
Table 12-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.42% 

26.52% 

26.09% 

0.42% 

70.00% 

69.58% 

0.42% 

70.00% 

69.58% 

0.42% 

70.00% 

69.58% 

0.42% 

70.00% 

69.58% 

Table 12-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.02% 

0.02% 

0.00% 

0.02% 

0.01% 

-0.01% 

0.02% 

0.01% 

-0.01% 

0.02% 

0.01% 

-0.01% 

0.02% 

0.01% 

-0.01% 

12.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 12-6 and Table 12-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 12-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

Table 12-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

99.55% 

73.47% 

-26.09% 

99.55% 

29.99% 

-69.56% 

99.55% 

29.99% 

-69.56% 

99.55% 

29.99% 

-69.56% 

99.55% 

29.99% 

-69.56% 

12.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 12-8.  

Table 12-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

3 

0 

0 

3 

0 

0 

3 

0 

0 

3 

0 

0 

3 

0 

0 

629 

672 

707 

743 

781 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

167 

473 

497 

522 

549 

0 

0 

464 

165 

0 

0 

0 

0 

203 

470 

0 

0 

0 

0 

213 

494 

0 

0 

0 

0 

224 

519 

0 

0 

0 

0 

235 

546 

0 

0 

-165 

-470 

-494 

-519 

-545 

Figure 12-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
offset by a decrease in landfill. 

Figure 12-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

12.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 12-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

28/05/2015 

63 

 
 
 
 
Table 12-9: Waste Collection and Treatment Unit Costs (2015 Real Term 
Prices), € per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 32.60 

€ 32.60 

€ 32.10 

€ 31.10 

€ 39.10 

€ 21.22 

€ 7.99 

€ 35.15 

€ 32.15 

€ 23.65 

€ 23.78 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 12-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 12-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

-€ 0.11 

-€ 0.15 

-€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 13.07 

-€ 0.88 

-€ 0.31 

-€ 0.43 

-€ 0.04 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 94.19 

-€ 2.94 

-€ 0.33 

-€ 0.45 

-€ 0.04 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 0.34 

-€ 0.47 

-€ 0.04 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 0.36 

-€ 0.49 

-€ 0.04 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 98.99 

€ 104.04 

€ 109.35 

-€ 3.09 

-€ 3.25 

-€ 3.42 

-€ 111.98 

-€ 161.56 

-€ 169.81 

-€ 178.47 

-€ 187.57 

€ 1.07 

€ 0.02 

-€ 669.58 

€ 2.94 

€ 3.09 

€ 3.25 

€ 3.41 

€ 0.05 
-€ 
1,996.59 
-€ 
2,708.81 
-€ 227.65 

€ 0.05 
-€ 
2,098.43 
-€ 
2,846.98 
-€ 239.26 

€ 0.05 
-€ 
2,205.47 
-€ 
2,992.21 
-€ 251.47 

€ 0.06 
-€ 
2,317.97 
-€ 
3,144.84 
-€ 264.29 

Mineral Waste and Asphalt 

-€ 970.19 

Other C&D 

-€ 75.79 

 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Total 

-€ 1,815 

-€ 5,001 

-€ 5,256 

-€ 5,524 

-€ 5,806 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

12.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 12-11. These costs reflect the combined impact of both 
the climate change impacts together with those impacts associated with other emissions to 
air such as NOx and PM. 

Table 12-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 26.27 

-€ 6.07 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 26.27 

-€ 6.07 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 26.27 

-€ 6.07 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 27.72 

-€ 6.32 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 38.33 

-€ 8.14 

-€ 95.31 

-€ 95.31 

-€ 95.31 

-€ 103.96 

-€ 167.38 

-€ 39.86 

-€ 39.86 

-€ 39.86 

-€ 45.78 

-€ 89.23 

-€ 69.06 

-€ 77.68 

-€ 89.45 

-€ 105.31 

-€ 124.86 

-€ 4.67 

-€ 4.67 

-€ 4.67 

-€ 4.74 

-€ 5.27 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 45.95 

-€ 45.95 

-€ 45.95 

-€ 49.34 

-€ 74.16 

-€ 6.68 

-€ 8.25 

-€ 8.25 

-€ 8.25 

-€ 6.68 

-€ 8.25 

-€ 8.25 

-€ 8.25 

-€ 6.68 

-€ 8.25 

-€ 8.25 

-€ 8.25 

-€ 6.97 

-€ 8.32 

-€ 8.32 

-€ 8.32 

-€ 9.10 

-€ 8.85 

-€ 8.85 

-€ 8.85 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 12-12. 

Table 12-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

0.48 

-0.08 

-2.88 

0.48 

-0.08 

-2.88 

0.48 

-0.08 

-2.88 

0.48 

-0.08 

-2.88 

0.48 

-0.08 

-2.88 

28/05/2015 

65 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

Mineral Waste and Asphalt 

Other C&D 

-1.98 

-0.38 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-1.98 

-0.38 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-1.98 

-0.38 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-1.98 

-0.38 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-1.98 

-0.38 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 12-13.   

Table 12-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and 
Asphalt 
Other C&D 

-€ 0.04 

-€ 0.11 

-€ 0.11 

-€ 0.12 

-€ 0.12 

-€ 0.05 

-€ 0.15 

-€ 0.15 

-€ 0.16 

-€ 0.17 

-€ 0.00 

-€ 0.01 

-€ 0.01 

-€ 0.01 

-€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 75.32 

-€ 610.41 

-€ 738.82 

-€ 914.16 

-€ 1,139.13 

-€ 0.28 

-€ 0.93 

-€ 0.98 

-€ 1.04 

-€ 1.22 

-€ 558.75 

-€ 806.12 

-€ 847.24 

-€ 970.76 

-€ 1,639.22 

-€ 9.49 

-€ 26.15 

-€ 27.48 

-€ 31.01 

-€ 48.99 

-€ 2.09 

-€ 501.33 

-€ 737.80 

-€ 57.64 

-€ 5.75 
-€ 
1,494.89 
-€ 
2,059.95 
-€ 173.12 

-€ 6.04 
-€ 
1,571.15 
-€ 
2,165.03 
-€ 181.95 

-€ 6.63 

-€ 9.10 

-€ 1,665.71 

-€ 1,861.85 

-€ 2,295.34 

-€ 2,565.61 

-€ 192.90 

-€ 215.62 

-€ 1,943 

-€ 5,178 

-€ 5,539 

-€ 6,078 

-€ 7,481 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 12-14. 

 
 
 
Table 12-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.00 

0.00 

0.00 

0.00 

-0.41 

0.00 

0.00 

0.00 

0.00 

0.00 

-2.97 

0.00 

0.00 

0.00 

0.00 

0.00 

-3.12 

-0.01 

0.00 

0.00 

0.00 

0.00 

-3.28 

-0.01 

0.00 

0.00 

0.00 

0.00 

-3.45 

-0.01 

-16.80 

-24.23 

-25.47 

-26.77 

-28.13 

-0.23 

-0.03 

-1.46 

-2.15 

-0.17 

-0.64 

-0.08 

-4.35 

-6.00 

-0.50 

-0.67 

-0.09 

-4.57 

-6.30 

-0.53 

-0.71 

-0.09 

-4.81 

-6.62 

-0.56 

-0.75 

-0.10 

-5.05 

-6.96 

-0.59 

Total 

-21.25 

-38.79 

-40.77 

-42.84 

-45.03 

Note: Positive values denote an increase in greenhouse gas emissions. 

12.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 12-2 and Table 12-15. From this 
it is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

28/05/2015 

67 

 
 
Figure 12-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

Table 12-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 1.94 

-€ 5.18 

-€ 5.54 

-€ 6.08 

-€ 7.48 

Financial Costs (social metric) 

-€ 1.81 

Net Costs and Benefits 

-€ 3.76 

-€ 5.00 
-€ 
10.18 

-€ 5.26 
-€ 
10.80 

-€ 5.52 
-€ 
11.60 

-€ 5.81 
-€ 
13.29 

-£70.0 

-£64.8 

-£134.9 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

 
 
 
 
 
 
13.0  Hungary 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 13-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €21 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 13-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 11.8 

-€ 10.9 

-€ 22.7 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

28/05/2015 

69 

 
 
                                                      
 
 
13.1  Waste Generation and Management Projections 

13.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.27,28 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 13-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 13-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

3,400 

1,974 

3,636 

2,111 

3,822 

2,219 

4,017 

2,332 

4,221 

2,451 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
Hungary. We therefore proceeded to undertake a qualitative assessment of waste 
compositions in Hungary and judged that a ‘High Mineral Waste’ composition would be 
most appropriate (Table 13-3). 

Table 13-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

13.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 13-4 and Table 
13-5. 

27 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
28 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
Table 13-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

65.29% 

67.06% 

1.77% 

65.29% 

70.00% 

4.71% 

65.29% 

70.00% 

4.71% 

65.29% 

70.00% 

4.71% 

65.29% 

70.00% 

4.71% 

Table 13-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Full Implementation (b) 

Difference (b-a) 

9.13% 

7.42% 

-1.71% 

9.13% 

4.56% 

-4.56% 

9.13% 

4.56% 

-4.56% 

9.13% 

4.56% 

-4.56% 

9.13% 

4.56% 

-4.56% 

13.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 13-6 and Table 13-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 13-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.07% 

0.07% 

0.00% 

0.07% 

0.07% 

0.00% 

0.07% 

0.07% 

0.00% 

0.07% 

0.07% 

0.00% 

0.07% 

0.07% 

0.00% 

Table 13-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

25.50% 

25.45% 

-0.05% 

25.50% 

25.36% 

-0.14% 

25.50% 

25.36% 

-0.14% 

25.50% 

25.36% 

-0.14% 

25.50% 

25.36% 

-0.14% 

13.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 13-8.  

Table 13-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

1,289 

1,378 

1,449 

1,523 

1,600 

180 

1 

504 

193 

2 

538 

203 

2 

566 

213 

2 

595 

224 

2 

625 

28/05/2015 

71 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

1,324 

1,478 

1,553 

1,632 

1,716 

146 

1 

502 

35 

-34 

0 

-1 

96 

2 

535 

99 

-96 

0 

-3 

101 

2 

563 

104 

-101 

0 

-3 

106 

2 

591 

110 

-106 

0 

-3 

112 

2 

622 

115 

-112 

0 

-3 

Figure 13-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
mostly offset by a decrease in backfilling, as well as a slight reduction in landfill. 

Figure 13-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

13.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 13-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

 
 
 
 
Table 13-9: Waste Collection and Treatment Unit Costs (2015 Real Term 
Prices), € per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 30.81 

€ 30.81 

€ 30.31 

€ 29.31 

€ 36.14 

€ 20.11 

€ 4.94 

€ 32.81 

€ 30.25 

€ 22.28 

€ 22.40 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 13-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 13-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Soil 

-€ 134.72 

-€ 384.16 

-€ 403.75 

-€ 424.35 

-€ 446.00 

Mineral Waste and Asphalt 

-€ 184.35 

-€ 525.70 

-€ 552.51 

-€ 580.70 

-€ 610.32 

Other C&D 

-€ 16.00 

-€ 45.63 

-€ 47.96 

-€ 50.41 

-€ 52.98 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Incineration 
to Recycling 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Switch from 
Landfill to 
Recycling 

Total 

€ 0.15 

€ 0.01 

-€ 0.01 

-€ 0.05 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.44 

€ 0.02 

-€ 0.04 

-€ 0.16 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.46 

€ 0.02 

-€ 0.04 

-€ 0.16 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 23.88 

€ 68.08 

€ 71.55 

-€ 0.19 

-€ 3.23 

€ 0.23 

-€ 0.01 

€ 6.03 

€ 9.87 

€ 0.72 

-€ 298 

-€ 0.53 

-€ 9.21 

€ 0.67 

-€ 0.02 

€ 17.19 

€ 28.15 

€ 2.04 

-€ 849 

-€ 0.56 

-€ 9.68 

€ 0.71 

-€ 0.02 

€ 18.07 

€ 29.59 

€ 2.15 

-€ 892 

€ 0.49 

€ 0.02 

-€ 0.04 

-€ 0.17 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 75.20 

-€ 0.59 

€ 0.51 

€ 0.02 

-€ 0.04 

-€ 0.18 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 79.04 

-€ 0.62 

-€ 10.17 

-€ 10.69 

€ 0.74 

-€ 0.02 

€ 18.99 

€ 31.09 

€ 2.26 

-€ 938 

€ 0.78 

-€ 0.02 

€ 19.96 

€ 32.68 

€ 2.37 

-€ 985 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

73 

 
13.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 13-11. These costs reflect the combined impact of both 
the climate change impacts together with those impacts associated with other emissions to 
air such as NOx and PM. 

Table 13-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

€ 10.99 

€ 10.99 

€ 10.99 

€ 11.59 

€ 15.99 

-€ 16.33 

-€ 16.33 

-€ 16.33 

-€ 16.50 

-€ 17.78 

-€ 104.19 

-€ 104.19 

-€ 104.19 

-€ 112.76 

-€ 175.63 

-€ 89.60 

-€ 89.60 

-€ 89.60 

-€ 97.61 

-€ 156.37 

-€ 57.53 

-€ 66.75 

-€ 79.90 

-€ 98.21 

-€ 120.37 

-€ 6.06 

-€ 6.06 

-€ 6.06 

-€ 6.13 

-€ 6.66 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 71.98 

-€ 71.98 

-€ 71.98 

-€ 75.36 

-€ 100.18 

-€ 6.68 

-€ 9.64 

-€ 9.64 

-€ 9.64 

-€ 6.68 

-€ 9.64 

-€ 9.64 

-€ 9.64 

-€ 6.68 

-€ 9.64 

-€ 9.64 

-€ 9.64 

-€ 6.97 

-€ 9.71 

-€ 9.71 

-€ 9.71 

-€ 9.10 

-€ 10.24 

-€ 10.24 

-€ 10.24 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 13-12. 

Table 13-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

0.20 

-0.06 

-2.86 

-2.67 

-0.52 

-0.02 

-2.82 

-1.13 

0.20 

-0.06 

-2.86 

-2.67 

-0.52 

-0.02 

-2.82 

-1.13 

0.20 

-0.06 

-2.86 

-2.67 

-0.52 

-0.02 

-2.82 

-1.13 

0.20 

-0.06 

-2.86 

-2.67 

-0.52 

-0.02 

-2.82 

-1.13 

0.20 

-0.06 

-2.86 

-2.67 

-0.52 

-0.02 

-2.82 

-1.13 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 13-13.   

Table 13-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

-€ 48.09 

-€ 137.13 

-€ 144.13 

-€ 151.48 

-€ 159.21 

-€ 66.88 

-€ 190.72 

-€ 200.45 

-€ 210.67 

-€ 221.42 

-€ 5.81 

-€ 16.56 

-€ 17.40 

-€ 18.29 

-€ 19.22 

€ 0.16 

€ 0.01 

-€ 0.06 

€ 1.04 

€ 0.48 

€ 0.02 

-€ 0.19 

€ 3.18 

€ 0.51 

€ 0.02 

-€ 0.20 

€ 3.34 

€ 0.56 

€ 0.02 

-€ 0.23 

€ 3.83 

€ 0.81 

€ 0.03 

-€ 0.37 

€ 6.45 

-€ 136.32 

-€ 450.83 

-€ 567.17 

-€ 732.68 

-€ 943.85 

-€ 0.08 

-€ 0.23 

-€ 0.24 

-€ 14.31 

-€ 40.79 

-€ 42.87 

-€ 3.81 

-€ 11.04 

-€ 11.60 

-€ 0.42 

-€ 1.19 

-€ 1.25 

€ 5.53 

€ 15.76 

€ 16.57 

-€ 0.26 

-€ 49.12 

-€ 12.77 

-€ 1.37 

€ 17.54 

-€ 0.29 

-€ 82.95 

-€ 17.84 

-€ 1.89 

€ 19.44 

€ 9.19 

€ 26.21 

€ 27.55 

€ 29.17 

€ 32.32 

€ 0.67 

-€ 259 

€ 1.90 

-€ 801 

€ 2.00 

-€ 935 

€ 2.12 

€ 2.35 

-€ 1,124 

-€ 1,386 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 13-14. 

Table 13-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

Plastics  

Switch from 

Wood 

28/05/2015 

0.00 

0.00 

0.00 

0.03 

-1.24 

0.01 

0.00 

-0.01 

0.09 

-3.54 

0.01 

0.00 

-0.01 

0.10 

-3.72 

0.01 

0.00 

-0.01 

0.10 

-3.91 

0.01 

0.00 

-0.01 

0.11 

-4.11 

75 

 
 
 
 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Landfill to 
Recycling 

Total 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.00 

-0.43 

-0.06 

-0.01 

0.01 

0.02 

0.00 

-1.67 

0.00 

-1.23 

-0.17 

-0.02 

0.04 

0.07 

0.00 

-4.75 

0.00 

-1.29 

-0.18 

-0.02 

0.04 

0.07 

0.00 

-4.99 

0.00 

-1.35 

-0.19 

-0.02 

0.04 

0.07 

0.01 

-5.24 

0.00 

-1.42 

-0.20 

-0.02 

0.05 

0.08 

0.01 

-5.51 

Note: Positive values denote an increase in greenhouse gas emissions. 

13.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 13-2 and Table 13-15. From this 
it is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

Figure 13-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

 
 
 
 
Table 13-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 0.26 

-€ 0.80 

-€ 0.94 

-€ 1.12 

-€ 1.39 

Financial Costs (social metric) 

-€ 0.30 

-€ 0.85 

-€ 0.89 

-€ 0.94 

-€ 0.99 

Net Costs and Benefits 

-€ 0.56 

-€ 1.65 

-€ 1.83 

-€ 2.06 

-€ 2.37 

-£11.8 

-€ 10.9 

-€ 22.7 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

77 

 
 
 
 
14.0 

Ireland 

According to Eurostat, the C&D recycling rate for Ireland was 74% in 2012.29,30 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

29 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
30 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
15.0 

Italy 

According to Eurostat, the C&D recycling rate for Italy was 96% in 2012.31,32 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

31 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
32 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

79 

 
 
 
                                                      
 
16.0  Latvia 

According to Eurostat, the C&D recycling rate for Latvia was 96% in 2012.33,34 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

33 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
34 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
17.0  Lithuania 

According to Eurostat, the C&D recycling rate for Lithuania was 85% in 2012.35,36 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

35 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
36 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

81 

 
 
 
                                                      
 
18.0  Luxembourg 

According to Eurostat, the C&D recycling rate for Luxembourg was 99% in 2012.37,38 This 
rate is above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

37 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
38 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
19.0  Malta 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 19-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €64 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 19-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 42.9 

-€ 31.8 

-€ 74.7 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

28/05/2015 

83 

 
 
                                                      
 
 
19.1  Waste Generation and Management Projections 

19.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.39,40 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 19-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 19-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

526 

573 

563 

612 

591 

644 

621 

676 

653 

711 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
Malta. We therefore proceeded to undertake a qualitative assessment of waste 
compositions in Malta and judged that a ‘High Mineral Waste’ composition would be most 
appropriate (Table 19-3). 

Table 19-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

19.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 19-4 and Table 
19-5. 

39 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
40 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
Table 19-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

19.43% 

38.40% 

18.96% 

19.43% 

70.00% 

50.57% 

19.43% 

70.00% 

50.57% 

19.43% 

70.00% 

50.57% 

19.43% 

70.00% 

50.57% 

Table 19-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Full Implementation (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

19.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 19-6 and Table 19-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 19-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

Table 19-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

80.57% 

61.60% 

-18.96% 

80.57% 

30.00% 

-50.57% 

80.57% 

30.00% 

-50.57% 

80.57% 

30.00% 

-50.57% 

80.57% 

30.00% 

-50.57% 

19.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 19-8.  

Table 19-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

111 

119 

125 

131 

138 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

461 

493 

519 

545 

573 

28/05/2015 

85 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

220 

429 

451 

473 

498 

0 

0 

353 

109 

0 

0 

0 

0 

184 

310 

0 

0 

0 

0 

193 

325 

0 

0 

0 

0 

203 

342 

0 

0 

0 

0 

213 

359 

0 

0 

-109 

-310 

-325 

-342 

-359 

Figure 19-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
offset by a decrease in landfill. 

Figure 19-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

19.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 19-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

 
 
 
 
Table 19-9: Waste Collection and Treatment Unit Costs (2015 Real Term 
Prices), € per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 31.97 

€ 31.97 

€ 31.47 

€ 30.47 

€ 38.74 

€ 20.97 

€ 8.10 

€ 34.51 

€ 31.53 

€ 23.17 

€ 23.30 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 19-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 19-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 3.50 

-€ 0.62 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 31.13 

-€ 1.40 

€ 32.71 

-€ 1.48 

€ 34.38 

-€ 1.55 

€ 36.14 

-€ 1.63 

-€ 41.14 

-€ 68.60 

-€ 72.10 

-€ 75.78 

-€ 79.64 

€ 0.21 

-€ 0.12 

€ 0.61 

-€ 0.34 

-€ 334.55 

-€ 968.95 

€ 0.64 

€ 0.67 

€ 0.71 

-€ 0.36 
-€ 
1,018.38 
-€ 
1,399.96 
-€ 120.92 

-€ 0.38 
-€ 
1,070.33 
-€ 
1,471.37 
-€ 127.09 

-€ 0.40 
-€ 
1,124.92 
-€ 
1,546.43 
-€ 133.57 

Mineral Waste and Asphalt 

-€ 478.58 

Other C&D 

-€ 40.79 

-€ 
1,332.01 
-€ 115.05 

28/05/2015 

87 

 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Total 

-€ 892 

-€ 2,455 

-€ 2,580 

-€ 2,711 

-€ 2,850 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

19.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 19-11. These costs reflect the combined impact of both 
the climate change impacts together with those impacts associated with other emissions to 
air such as NOx and PM. 

Table 19-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 31.66 

-€ 5.35 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 31.66 

-€ 5.35 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 31.66 

-€ 5.35 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 33.08 

-€ 5.59 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 43.47 

-€ 7.40 

-€ 94.74 

-€ 94.74 

-€ 94.74 

-€ 103.39 

-€ 166.78 

-€ 25.85 

-€ 25.85 

-€ 25.85 

-€ 31.85 

-€ 75.84 

-€ 72.43 

-€ 81.15 

-€ 93.07 

-€ 109.12 

-€ 128.87 

-€ 4.53 

-€ 4.53 

-€ 4.53 

-€ 4.60 

-€ 5.13 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 43.83 

-€ 43.83 

-€ 43.83 

-€ 47.21 

-€ 72.03 

-€ 6.68 

-€ 8.11 

-€ 8.11 

-€ 8.11 

-€ 6.68 

-€ 8.11 

-€ 8.11 

-€ 8.11 

-€ 6.68 

-€ 8.11 

-€ 8.11 

-€ 8.11 

-€ 6.97 

-€ 8.18 

-€ 8.18 

-€ 8.18 

-€ 9.10 

-€ 8.71 

-€ 8.71 

-€ 8.71 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 19-12. 

Table 19-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

0.47 

-0.08 

-2.88 

0.47 

-0.08 

-2.88 

0.47 

-0.08 

-2.88 

0.47 

-0.08 

-2.88 

0.47 

-0.08 

-2.88 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

Mineral Waste and Asphalt 

Other C&D 

-2.00 

-0.33 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.00 

-0.33 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.00 

-0.33 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.00 

-0.33 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.00 

-0.33 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 19-13.   

Table 19-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and 
Asphalt 
Other C&D 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 51.70 

-€ 514.95 

-€ 620.72 

-€ 764.83 

-€ 949.37 

-€ 0.28 

-€ 0.64 

-€ 0.67 

-€ 0.72 

-€ 0.84 

-€ 149.19 

-€ 248.75 

-€ 261.44 

-€ 299.55 

-€ 505.82 

-€ 5.64 

-€ 16.09 

-€ 16.91 

-€ 19.15 

-€ 30.71 

-€ 1.30 

-€ 3.71 

-€ 333.40 

-€ 965.63 

-€ 483.89 

-€ 41.24 

-€ 
1,346.79 
-€ 116.33 

-€ 3.90 
-€ 
1,014.89 
-€ 
1,415.49 
-€ 122.26 

-€ 4.28 

-€ 5.87 

-€ 1,076.14 

-€ 1,204.13 

-€ 1,500.93 

-€ 1,679.43 

-€ 129.64 

-€ 145.06 

-€ 1,067 

-€ 3,213 

-€ 3,456 

-€ 3,795 

-€ 4,521 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 19-14. 

28/05/2015 

89 

 
 
 
Table 19-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

0.00 

0.00 

0.00 

0.00 

-0.23 

0.00 

-4.48 

-0.15 

-0.02 

-0.99 

-1.43 

-0.12 

-7.43 

0.00 

0.00 

0.00 

0.00 

-2.08 

0.00 

-7.48 

-0.41 

-0.05 

-2.86 

-3.99 

-0.34 

0.00 

0.00 

0.00 

0.00 

-2.19 

0.00 

-7.86 

-0.44 

-0.06 

-3.01 

-4.20 

-0.36 

0.00 

0.00 

0.00 

0.00 

-2.30 

0.00 

-8.26 

-0.46 

-0.06 

-3.16 

-4.41 

-0.38 

0.00 

0.00 

0.00 

0.00 

-2.42 

0.00 

-8.68 

-0.48 

-0.06 

-3.32 

-4.63 

-0.40 

-17.23 

-18.11 

-19.03 

-20.00 

Note: Positive values denote an increase in greenhouse gas emissions. 

19.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 19-2 and Table 19-15. From this 
it is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

 
 
Figure 19-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

Table 19-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 1.07 

-€ 3.21 

-€ 3.46 

-€ 3.80 

-€ 4.52 

Financial Costs (social metric) 

-€ 0.89 

-€ 2.45 

-€ 2.58 

-€ 2.71 

-€ 2.85 

Net Costs and Benefits 

-€ 1.96 

-€ 5.67 

-€ 6.04 

-€ 6.51 

-€ 7.37 

-€ 42.9 

-€ 31.8 

-€ 74.7 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

91 

 
 
 
 
 
 
20.0  Netherlands 

According to Eurostat, the C&D recycling rate for the Netherlands was 100% in 2012.41,42 
This rate is above the 70% recycling target specified by the ‘More Ambitious’ scenario and 
was therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

41 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
42 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
21.0  Poland 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 21-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €29 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 21-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 27.3 

-€ 4.5 

-€ 31.8 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

28/05/2015 

93 

 
 
                                                      
 
 
21.1  Waste Generation and Management Projections 

21.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.43,44 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 21-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 21-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

3,712 

3,190 

3,969 

3,411 

4,172 

3,585 

4,385 

3,768 

4,608 

3,960 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

The C&D waste composition for Poland reported in the literature is most similar to the ‘High 
Wood’ composition, and therefore this compositional set was used for modelling (Table 
21-3).45 

Table 21-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Wood 

26.0% 

0.1% 

9.4% 

1.5% 

2.3% 

30.6% 

24.1% 

6.0% 

21.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 21-4 and Table 
21-5. 

43 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
44 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 
45 ETC/SCP (2009) EU as a Recycling Society: Present Recycling Levels of Municipal Waste and Construction & 
Demolition Waste in the EU, April 2009, http://scp.eionet.europa.eu/publications/wp2009_2/wp/WP2009_2 

 
 
 
                                                      
 
Table 21-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

67.77% 

68.61% 

0.84% 

67.77% 

70.00% 

2.23% 

67.77% 

70.00% 

2.23% 

67.77% 

70.00% 

2.23% 

67.77% 

70.00% 

2.23% 

Table 21-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Full Implementation (b) 

Difference (b-a) 

24.32% 

23.49% 

-0.84% 

24.32% 

22.10% 

-2.23% 

24.32% 

22.10% 

-2.23% 

24.32% 

22.10% 

-2.23% 

24.32% 

22.10% 

-2.23% 

21.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 21-6 and Table 21-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 21-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.17% 

0.17% 

0.00% 

0.17% 

0.17% 

0.00% 

0.17% 

0.17% 

0.00% 

0.17% 

0.17% 

0.00% 

0.17% 

0.17% 

0.00% 

Table 21-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

7.73% 

7.73% 

0.00% 

7.73% 

7.73% 

0.00% 

7.73% 

7.73% 

0.00% 

7.73% 

7.73% 

0.00% 

7.73% 

7.73% 

0.00% 

21.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 21-8.  

Table 21-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

2,162 

2,312 

2,429 

2,553 

2,684 

776 

5 

247 

830 

6 

264 

872 

6 

277 

916 

6 

291 

963 

7 

306 

28/05/2015 

95 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

2,188 

2,388 

2,509 

2,637 

2,772 

749 

5 

247 

27 

-27 

0 

0 

754 

6 

264 

76 

-76 

0 

0 

792 

6 

277 

80 

-80 

0 

0 

833 

6 

291 

84 

-84 

0 

0 

875 

7 

306 

88 

-88 

0 

0 

Figure 21-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
offset by a decrease in backfilling. 

Figure 21-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

21.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 21-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

 
 
 
 
Table 21-9: Waste Collection and Treatment Unit Costs (2015 Real Term 
Prices), € per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 29.10 

€ 29.10 

€ 28.60 

€ 27.60 

€ 34.01 

€ 19.19 

€ 3.20 

€ 30.77 

€ 28.49 

€ 20.97 

€ 21.08 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 21-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 21-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Soil 

-€ 98.36 

-€ 280.49 

-€ 294.79 

-€ 309.83 

-€ 325.63 

Mineral Waste and Asphalt 

-€ 76.53 

-€ 218.22 

-€ 229.35 

-€ 241.05 

-€ 253.35 

Other C&D 

-€ 19.02 

-€ 54.24 

-€ 57.01 

-€ 59.92 

-€ 62.97 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Incineration 
to Recycling 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Switch from 
Landfill to 
Recycling 

Total 

€ 0.04 

€ 0.00 

-€ 0.09 

-€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 31.39 

-€ 0.16 

€ 0.11 

€ 0.01 

-€ 0.27 

-€ 0.04 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 89.51 

-€ 0.45 

€ 0.11 

€ 0.01 

-€ 0.28 

-€ 0.05 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 94.07 

-€ 0.47 

€ 0.12 

€ 0.01 

-€ 0.29 

-€ 0.05 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.12 

€ 0.02 

-€ 0.31 

-€ 0.05 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 98.87 

€ 103.91 

-€ 0.49 

-€ 0.52 

-€ 26.54 

-€ 75.68 

-€ 79.54 

-€ 83.59 

-€ 87.86 

€ 0.12 

-€ 0.05 

€ 34.92 

€ 24.26 

€ 7.99 

-€ 122 

€ 0.34 

-€ 0.15 

€ 0.36 

-€ 0.16 

€ 0.38 

-€ 0.17 

€ 0.40 

-€ 0.18 

€ 99.58 

€ 104.66 

€ 110.00 

€ 115.61 

€ 69.18 

€ 22.80 

-€ 348 

€ 72.71 

€ 23.96 

-€ 366 

€ 76.42 

€ 25.18 

-€ 384 

€ 80.32 

€ 26.47 

-€ 404 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

97 

 
21.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 21-11. These costs reflect the combined impact of both 
the climate change impacts together with those impacts associated with other emissions to 
air such as NOx and PM. 

Table 21-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

€ 55.80 

€ 55.80 

€ 55.80 

€ 57.81 

€ 72.53 

-€ 14.64 

-€ 14.64 

-€ 14.64 

-€ 14.94 

-€ 17.13 

-€ 103.18 

-€ 103.18 

-€ 103.18 

-€ 111.88 

-€ 175.66 

€ 25.85 

€ 25.85 

€ 25.85 

€ 21.30 

-€ 12.03 

-€ 58.16 

-€ 67.09 

-€ 79.84 

-€ 97.59 

-€ 119.11 

-€ 5.37 

-€ 5.37 

-€ 5.37 

-€ 5.45 

-€ 5.97 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 60.21 

-€ 60.21 

-€ 60.21 

-€ 63.60 

-€ 88.42 

-€ 6.68 

-€ 8.95 

-€ 8.95 

-€ 8.95 

-€ 6.68 

-€ 8.95 

-€ 8.95 

-€ 8.95 

-€ 6.68 

-€ 8.95 

-€ 8.95 

-€ 8.95 

-€ 6.97 

-€ 9.03 

-€ 9.03 

-€ 9.03 

-€ 9.10 

-€ 9.55 

-€ 9.55 

-€ 9.55 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 21-12. 

Table 21-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

0.67 

-0.10 

-2.90 

-1.51 

-0.46 

-0.02 

-2.82 

-1.13 

0.67 

-0.10 

-2.90 

-1.51 

-0.46 

-0.02 

-2.82 

-1.13 

0.67 

-0.10 

-2.90 

-1.51 

-0.46 

-0.02 

-2.82 

-1.13 

0.67 

-0.10 

-2.90 

-1.51 

-0.46 

-0.02 

-2.82 

-1.13 

0.67 

-0.10 

-2.90 

-1.51 

-0.46 

-0.02 

-2.82 

-1.13 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 21-13.   

Table 21-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

-€ 47.94 

-€ 136.69 

-€ 143.66 

-€ 150.99 

-€ 158.69 

-€ 37.87 

-€ 107.99 

-€ 113.49 

-€ 119.28 

-€ 125.37 

-€ 9.41 

-€ 26.84 

-€ 28.21 

-€ 29.65 

-€ 31.16 

€ 0.47 

€ 0.01 

-€ 0.35 

-€ 0.29 

-€ 433.17 

-€ 0.09 

€ 1.40 

€ 0.02 

€ 1.47 

€ 0.02 

-€ 1.03 

-€ 1.09 

-€ 0.87 
-€ 
1,424.86 
-€ 0.26 

-€ 0.91 
-€ 
1,782.05 
-€ 0.27 

€ 1.60 

€ 0.02 

-€ 1.24 

-€ 0.79 

€ 2.11 

€ 0.03 

-€ 2.04 

€ 0.47 

-€ 2,289.36 

-€ 2,936.88 

-€ 0.29 

-€ 0.33 

-€ 93.87 

-€ 267.63 

-€ 281.29 

-€ 322.30 

-€ 544.22 

-€ 5.51 

-€ 15.77 

-€ 16.58 

-€ 18.40 

-€ 26.89 

-€ 0.53 

-€ 1.50 

-€ 1.58 

-€ 1.73 

-€ 2.37 

€ 39.92 

€ 113.83 

€ 119.63 

€ 126.75 

€ 141.01 

€ 28.13 

€ 80.22 

€ 84.31 

€ 89.33 

€ 99.38 

€ 9.27 

-€ 551 

€ 26.43 

€ 27.78 

€ 29.43 

€ 32.75 

-€ 1,762 

-€ 2,136 

-€ 2,687 

-€ 3,552 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 21-14. 

28/05/2015 

99 

 
 
 
Table 21-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.01 

0.00 

-0.01 

0.02 

-3.46 

0.00 

-2.82 

-0.10 

-0.01 

0.11 

0.08 

0.02 

0.02 

0.00 

-0.03 

0.05 

-9.86 

0.00 

-8.05 

-0.30 

-0.02 

0.31 

0.22 

0.07 

0.02 

0.00 

-0.03 

0.05 

0.02 

0.00 

-0.03 

0.06 

0.02 

0.00 

-0.03 

0.06 

-10.36 

-10.89 

-11.45 

0.00 

-8.46 

-0.31 

-0.02 

0.32 

0.23 

0.07 

0.00 

-8.89 

-0.33 

-0.02 

0.34 

0.24 

0.08 

0.00 

-9.34 

-0.34 

-0.03 

0.35 

0.25 

0.08 

Total 

-6.17 

-17.59 

-18.49 

-19.43 

-20.42 

Note: Positive values denote an increase in greenhouse gas emissions. 

21.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 21-2 and Table 21-15. From this 
it is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

 
 
Figure 21-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

Table 21-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 0.55 

-€ 1.76 

-€ 2.14 

-€ 2.69 

-€ 3.55 

Financial Costs (social metric) 

-€ 0.12 

-€ 0.35 

-€ 0.37 

-€ 0.38 

-€ 0.40 

Net Costs and Benefits 

-€ 0.67 

-€ 2.11 

-€ 2.50 

-€ 3.07 

-€ 3.96 

-€ 27.3 

-€ 4.5 

-€ 31.8 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

101 

 
 
 
 
 
 
22.0  Portugal 

According to Eurostat, the C&D recycling rate for Portugal was 74% in 2012.46,47 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

46 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
47 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
23.0  Romania 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 23-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €9.2 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 23-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 5.2 

-€ 2.5 

-€ 7.8 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

28/05/2015 

103 

 
 
                                                      
 
 
23.1  Waste Generation and Management Projections 

23.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.48,49 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 23-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 23-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

1,446 

859 

1,546 

919 

1,625 

966 

1,708 

1,015 

1,795 

1,067 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
Romania. We therefore proceeded to undertake a qualitative assessment of waste 
compositions in Romania and judged that a ‘High Mineral Waste’ composition would be 
most appropriate (Table 23-3). 

Table 23-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

23.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 23-4 and Table 
23-5. 

48 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
49 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
 
                                                      
 
Table 23-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

67.25% 

68.28% 

1.03% 

67.25% 

70.00% 

2.75% 

67.25% 

70.00% 

2.75% 

67.25% 

70.00% 

2.75% 

67.25% 

70.00% 

2.75% 

Table 23-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Full Implementation (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

23.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 23-6 and Table 23-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 23-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

Table 23-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

32.75% 

31.72% 

-1.03% 

32.75% 

30.00% 

-2.75% 

32.75% 

30.00% 

-2.75% 

32.75% 

30.00% 

-2.75% 

32.75% 

30.00% 

-2.75% 

23.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 23-8.  

Table 23-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

578 

618 

650 

683 

718 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

281 

301 

316 

332 

349 

28/05/2015 

105 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

587 

643 

676 

711 

747 

0 

0 

273 

9 

0 

0 

-9 

0 

0 

276 

25 

0 

0 

-25 

0 

0 

290 

27 

0 

0 

-27 

0 

0 

305 

28 

0 

0 

-28 

0 

0 

320 

29 

0 

0 

-29 

Figure 23-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
offset by a decrease in landfill. 

Figure 23-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

23.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 23-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

 
 
 
 
Table 23-9: Waste Collection and Treatment Unit Costs (2015 Real Term 
Prices), € per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 27.81 

€ 27.81 

€ 27.31 

€ 26.31 

€ 32.03 

€ 18.42 

€ 1.25 

€ 29.12 

€ 27.13 

€ 19.98 

€ 20.09 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 23-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 23-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 4.02 

-€ 0.04 

-€ 0.94 

€ 0.03 

-€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 11.46 

€ 12.05 

€ 12.66 

€ 13.31 

-€ 0.10 

-€ 2.68 

€ 0.08 

-€ 0.02 

-€ 0.11 

-€ 2.82 

€ 0.08 

-€ 0.02 

-€ 0.11 

-€ 2.96 

€ 0.08 

-€ 0.02 

-€ 0.12 

-€ 3.11 

€ 0.09 

-€ 0.02 

-€ 28.98 

-€ 82.64 

-€ 86.85 

-€ 91.28 

-€ 95.94 

Mineral Waste and Asphalt 

-€ 39.37 

-€ 112.25 

-€ 117.98 

-€ 124.00 

-€ 130.32 

Other C&D 

Total 

-€ 3.45 

-€ 69 

-€ 9.83 

-€ 196 

-€ 10.33 

-€ 10.86 

-€ 11.41 

-€ 206 

-€ 216 

-€ 228 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

107 

 
23.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 23-11. These costs reflect the combined impact of both 
the climate change impacts together with those impacts associated with other emissions to 
air such as NOx and PM. 

Table 23-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

-€ 3.57 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

€ 14.35 

€ 14.35 

€ 14.35 

€ 15.04 

€ 20.13 

-€ 13.44 

-€ 13.44 

-€ 13.44 

-€ 13.62 

-€ 14.96 

-€ 101.69 

-€ 101.69 

-€ 101.69 

-€ 110.27 

-€ 173.19 

-€ 77.81 

-€ 77.81 

-€ 77.81 

-€ 85.59 

-€ 142.66 

-€ 75.85 

-€ 85.05 

-€ 98.17 

-€ 116.44 

-€ 138.56 

-€ 5.67 

-€ 5.67 

-€ 5.67 

-€ 5.74 

-€ 6.27 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 64.63 

-€ 64.63 

-€ 64.63 

-€ 68.01 

-€ 92.83 

-€ 6.68 

-€ 9.25 

-€ 9.25 

-€ 9.25 

-€ 6.68 

-€ 9.25 

-€ 9.25 

-€ 9.25 

-€ 6.68 

-€ 9.25 

-€ 9.25 

-€ 9.25 

-€ 6.97 

-€ 9.32 

-€ 9.32 

-€ 9.32 

-€ 9.10 

-€ 9.85 

-€ 9.85 

-€ 9.85 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 23-12. 

Table 23-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

0.23 

-0.06 

-2.86 

-2.59 

-0.52 

-0.02 

-2.82 

-1.13 

0.23 

-0.06 

-2.86 

-2.59 

-0.52 

-0.02 

-2.82 

-1.13 

0.23 

-0.06 

-2.86 

-2.59 

-0.52 

-0.02 

-2.82 

-1.13 

0.23 

-0.06 

-2.86 

-2.59 

-0.52 

-0.02 

-2.82 

-1.13 

0.23 

-0.06 

-2.86 

-2.59 

-0.52 

-0.02 

-2.82 

-1.13 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 23-13.   

Table 23-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 0.00 

-€ 0.00 

-€ 0.00 

€ 0.00 

€ 0.01 

-€ 0.00 

-€ 0.01 

-€ 0.01 

€ 0.00 

€ 0.01 

-€ 0.00 

-€ 0.01 

-€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.01 

-€ 0.00 

-€ 0.01 

-€ 0.01 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.02 

-€ 0.00 

-€ 0.01 

-€ 0.01 

-€ 45.94 

-€ 146.90 

-€ 178.22 

-€ 222.16 

-€ 277.86 

-€ 0.02 

-€ 0.05 

-€ 0.06 

-€ 0.06 

-€ 0.07 

-€ 3.65 

-€ 10.41 

-€ 10.94 

-€ 12.53 

-€ 21.16 

-€ 0.68 

-€ 0.11 

-€ 1.93 

-€ 0.30 

-€ 2.03 

-€ 0.32 

-€ 2.24 

-€ 0.35 

-€ 3.22 

-€ 0.48 

-€ 30.29 

-€ 86.37 

-€ 90.78 

-€ 96.15 

-€ 106.79 

-€ 41.76 

-€ 119.08 

-€ 125.15 

-€ 132.56 

-€ 147.23 

-€ 3.66 

-€ 10.43 

-€ 10.96 

-€ 11.61 

-€ 12.89 

-€ 126 

-€ 375 

-€ 418 

-€ 478 

-€ 570 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 23-14. 

Table 23-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

Plastics  

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

Switch from 

Wood 

-0.31 

-0.90 

-0.94 

-0.99 

-1.04 

28/05/2015 

109 

 
 
 
 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Landfill to 
Recycling 

Total 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.00 

-0.11 

-0.01 

0.00 

-0.08 

-0.11 

-0.01 

-0.63 

0.00 

-0.31 

-0.03 

0.00 

-0.22 

-0.31 

-0.03 

-1.81 

0.00 

-0.33 

-0.04 

0.00 

-0.24 

-0.33 

-0.03 

-1.90 

0.00 

-0.35 

-0.04 

0.00 

-0.25 

-0.34 

-0.03 

-2.00 

0.00 

-0.36 

-0.04 

-0.01 

-0.26 

-0.36 

-0.03 

-2.10 

Note: Positive values denote an increase in greenhouse gas emissions. 

23.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 23-2 and Table 23-15. From this 
it is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

Figure 23-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

 
 
 
 
Table 23-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 0.13 

-€ 0.38 

-€ 0.42 

-€ 0.48 

-€ 0.57 

Financial Costs (social metric) 

-€ 0.07 

-€ 0.20 

-€ 0.21 

-€ 0.22 

-€ 0.23 

Net Costs and Benefits 

-€ 0.19 

-€ 0.57 

-€ 0.62 

-€ 0.69 

-€ 0.80 

-€ 5.2 

-€ 2.5 

-€ 7.8 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

28/05/2015 

111 

 
 
 
 
24.0  Slovakia 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 24-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €29 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 24-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 23.9 

-€ 18.3 

-€ 42.2 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

 
 
                                                      
 
 
24.1  Waste Generation and Management Projections 

24.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.50,51 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 24-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 24-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

534 

445 

571 

476 

600 

500 

631 

525 

663 

552 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
Slovakia. We therefore proceeded to undertake a qualitative assessment of waste 
compositions in Slovakia and judged that a ‘High Mineral Waste’ composition would be 
most appropriate (Table 24-3). 

Table 24-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

24.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 24-4 and Table 
24-5. 

50 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
51 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

113 

 
 
 
                                                      
 
Table 24-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

38.64% 

50.40% 

11.76% 

38.64% 

70.00% 

31.36% 

38.64% 

70.00% 

31.36% 

38.64% 

70.00% 

31.36% 

38.64% 

70.00% 

31.36% 

Table 24-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Full Implementation (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

24.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 24-6 and Table 24-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 24-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.06% 

0.05% 

-0.01% 

0.06% 

0.03% 

-0.03% 

0.06% 

0.03% 

-0.03% 

0.06% 

0.03% 

-0.03% 

0.06% 

0.03% 

-0.03% 

Table 24-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

61.30% 

49.55% 

-11.75% 

61.30% 

29.97% 

-31.33% 

61.30% 

29.97% 

-31.33% 

61.30% 

29.97% 

-31.33% 

61.30% 

29.97% 

-31.33% 

24.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 24-8.  

Table 24-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

172 

184 

193 

203 

213 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

273 

292 

306 

322 

338 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

224 

333 

350 

368 

386 

0 

0 

220 

52 

0 

0 

-52 

0 

0 

143 

149 

0 

0 

0 

0 

150 

157 

0 

0 

0 

0 

157 

165 

0 

0 

0 

0 

165 

173 

0 

0 

-149 

-157 

-165 

-173 

Figure 24-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
offset by a decrease in landfill. 

Figure 24-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

24.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 24-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

28/05/2015 

115 

 
 
 
 
Table 24-9: Waste Collection and Treatment Unit Costs (2015 Real Term 
Prices), € per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 29.33 

€ 29.33 

€ 28.83 

€ 27.83 

€ 34.14 

€ 19.28 

€ 3.17 

€ 31.00 

€ 28.71 

€ 21.15 

€ 21.26 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 24-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 24-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.32 

-€ 0.01 

-€ 0.15 

€ 0.04 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 2.87 

-€ 0.28 

-€ 6.46 

€ 0.20 

-€ 0.02 

€ 0.00 

€ 0.00 

€ 0.00 

€ 1.00 

-€ 0.03 

-€ 0.33 

€ 0.08 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 36.86 

-€ 0.74 

€ 0.00 

€ 0.00 

€ 0.00 

€ 1.05 

-€ 0.03 

-€ 0.34 

€ 0.09 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 38.74 

-€ 0.78 

€ 0.00 

€ 0.00 

€ 0.00 

€ 1.11 

-€ 0.03 

-€ 0.36 

€ 0.09 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 40.71 

-€ 0.82 

€ 0.00 

€ 0.00 

€ 0.00 

€ 1.16 

-€ 0.03 

-€ 0.38 

€ 0.10 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 42.79 

-€ 0.86 

-€ 16.03 

-€ 16.85 

-€ 17.71 

-€ 18.61 

€ 0.58 

-€ 0.06 

€ 0.61 

-€ 0.06 

€ 0.64 

-€ 0.07 

€ 0.68 

-€ 0.07 

-€ 206.76 

-€ 581.68 

-€ 611.35 

-€ 642.54 

-€ 675.31 

Mineral Waste and Asphalt 

-€ 283.13 

-€ 781.80 

-€ 821.68 

-€ 863.59 

-€ 907.64 

Other C&D 

Total 

-€ 23.20 

-€ 517 

-€ 68.05 

-€ 1,410 

-€ 71.52 

-€ 1,482 

-€ 75.17 

-€ 79.00 

-€ 1,558 

-€ 1,637 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

 
24.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 24-11. These costs reflect the combined impact of both 
the climate change impacts together with those impacts associated with other emissions to 
air such as NOx and PM. 

Table 24-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 3.70 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 3.70 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 3.70 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 3.98 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 6.06 

-€ 14.12 

-€ 14.12 

-€ 14.12 

-€ 14.26 

-€ 15.33 

-€ 102.19 

-€ 102.19 

-€ 102.19 

-€ 110.73 

-€ 173.39 

-€ 105.34 

-€ 105.34 

-€ 105.34 

-€ 114.14 

-€ 178.62 

-€ 75.24 

-€ 84.52 

-€ 97.76 

-€ 116.20 

-€ 138.51 

-€ 5.85 

-€ 5.85 

-€ 5.85 

-€ 5.92 

-€ 6.45 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 67.89 

-€ 67.89 

-€ 67.89 

-€ 71.27 

-€ 96.09 

-€ 6.68 

-€ 9.43 

-€ 9.43 

-€ 9.43 

-€ 6.68 

-€ 9.43 

-€ 9.43 

-€ 9.43 

-€ 6.68 

-€ 9.43 

-€ 9.43 

-€ 9.43 

-€ 6.97 

-€ 9.50 

-€ 9.50 

-€ 9.50 

-€ 9.10 

-€ 10.03 

-€ 10.03 

-€ 10.03 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 24-12. 

Table 24-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

28/05/2015 

0.09 

-0.05 

-2.85 

-2.93 

-0.54 

-0.02 

-2.82 

-1.13 

0.09 

-0.05 

-2.85 

-2.93 

-0.54 

-0.02 

-2.82 

-1.13 

0.09 

-0.05 

-2.85 

-2.93 

-0.54 

-0.02 

-2.82 

-1.13 

0.09 

-0.05 

-2.85 

-2.93 

-0.54 

-0.02 

-2.82 

-1.13 

0.09 

-0.05 

-2.85 

-2.93 

-0.54 

-0.02 

-2.82 

-1.13 

117 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 24-13.   

Table 24-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.13 

-€ 0.01 

-€ 0.70 

-€ 1.02 

€ 0.00 

€ 0.42 

-€ 0.03 

-€ 1.46 

-€ 2.34 

€ 0.00 

€ 0.45 

-€ 0.03 

-€ 1.54 

-€ 2.46 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.50 

-€ 0.03 

-€ 1.75 

-€ 2.80 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.81 

-€ 0.03 

-€ 2.89 

-€ 4.60 

-€ 24.65 

-€ 356.09 

-€ 432.88 

-€ 540.74 

-€ 677.44 

-€ 0.12 

-€ 0.33 

-€ 0.34 

-€ 0.36 

-€ 0.42 

-€ 26.73 

-€ 66.33 

-€ 69.72 

-€ 79.88 

-€ 134.89 

-€ 3.55 

-€ 10.50 

-€ 11.03 

-€ 12.18 

-€ 17.25 

-€ 0.63 

-€ 1.79 

-€ 1.88 

-€ 2.06 

-€ 2.83 

-€ 193.72 

-€ 544.99 

-€ 572.79 

-€ 606.61 

-€ 673.03 

-€ 269.35 

-€ 743.75 

-€ 781.69 

-€ 827.84 

-€ 918.49 

-€ 22.07 

-€ 64.73 

-€ 68.04 

-€ 542 

-€ 1,792 

-€ 1,942 

-€ 72.05 

-€ 2,146 

-€ 79.94 

-€ 2,511 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 24-14. 

Table 24-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

Plastics  

Switch from 

Wood 

0.00 

0.00 

-0.02 

-0.03 

-0.18 

0.01 

0.00 

-0.04 

-0.07 

-2.26 

0.01 

0.00 

-0.04 

-0.07 

-2.38 

0.01 

0.00 

-0.05 

-0.07 

-2.50 

0.01 

0.00 

-0.05 

-0.08 

-2.63 

 
 
 
 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Landfill to 
Recycling 

Total 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.00 

-0.80 

-0.06 

-0.01 

-0.49 

-0.69 

-0.06 

-2.33 

0.00 

-1.99 

-0.17 

-0.03 

-1.39 

-1.90 

-0.16 

-8.00 

0.00 

-2.10 

-0.18 

-0.03 

-1.46 

-1.99 

-0.17 

-8.41 

0.00 

-2.20 

-0.19 

-0.03 

-1.53 

-2.09 

-0.18 

-8.84 

0.00 

-2.32 

-0.20 

-0.03 

-1.61 

-2.20 

-0.19 

-9.29 

Note: Positive values denote an increase in greenhouse gas emissions. 

24.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 24-2 and Table 24-15. From this 
it is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

Figure 24-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

28/05/2015 

119 

 
 
 
 
Table 24-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 0.54 

-€ 1.79 

-€ 1.94 

-€ 2.15 

-€ 2.51 

Financial Costs (social metric) 

-€ 0.52 

-€ 1.41 

-€ 1.48 

-€ 1.56 

-€ 1.64 

Net Costs and Benefits 

-€ 1.06 

-€ 3.20 

-€ 3.42 

-€ 3.70 

-€ 4.15 

-€ 23.9 

-€ 18.3 

-€ 42.2 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

 
 
 
 
25.0  Slovenia 

According to Eurostat, the C&D recycling rate for Slovenia was 91% in 2012.52,53 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

52 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
53 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

121 

 
 
 
                                                      
 
26.0  Spain 

This country report aims to provide an overview of the key country specific assumptions, 
and presents detailed model outputs, from the Construction & Demolition (C&D) Waste 
Model. The intention is to help Member States understand the key parameters which 
underpin the analysis and how the model results are calculated. It is hoped that that this 
summary report will provide greater transparency and clarity in the results, and 
demonstrate what type of outputs can be generated by the C&D Waste Model. This report 
should be read in conjunction with Appendix 1 which introduces the C&D Waste Model and 
explains the key sources of data that have been used and the assumptions which have been 
made.  

Modelling results are presented for a ‘More Ambitious’ scenario, which models a recycling 
target of 70% in 2020 for C&D waste. In contrast to the current Waste Framework Directive 
(WFD) target (included in the model as the ‘Full Implementation’ scenario), which includes 
preparation for reuse, recycling and other material recovery, the ‘More Ambitious’ scenario 
does not allow backfilling to count towards the target, and therefore requires more waste to 
be recycled in order to meet the target. All results are shown relative to a ‘Business as 
Usual’ scenario, which assumes that recycling and backfilling rates stay constant relative to 
current performance in the future. 

Table 26-1 shows the overall results from the cost-benefit analysis (CBA). For the ‘More 
Ambitious’ scenario, the model suggests a net benefit to society (relative to the ‘Business as 
Usual’ scenario) of around €120 million, in 2015 real term prices, over the period from 2015 
to 2035 in net present value terms. 

Table 26-1: Business as Usual vs More Ambitious Scenario, Change in Net 
Present Value, 2015 to 2035 (€ Million, 2015 Prices) 

Cost 

Net Present Value1 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Notes: 

-€ 61.8 

-€ 58.1 

-€ 119.9 

1.  The Net Present Value (NPV) is the current value of the total stream of costs and benefits in each year 

from 2015 to 2030, with future years discounted at the social discount rate of 4%. 
2.  Negative costs denote savings/benefits to society, whilst positive costs denote an overall 

cost/disbenefit to society. 

The following sections outline the intermediate results that help explain the model results.  

 
 
                                                      
 
 
26.1  Waste Generation and Management Projections 

26.1.1  Waste Flow Projections 

Waste data for 2012 was downloaded from Eurostat and this was used as the basis for all 
waste flow calculations.54,55 The assumed waste generation and treatment projections used 
for calculating the results are presented in Table 26-2. For more details on the growth rates 
used for these projections please refer to the discussion in Appendix 1. 

Table 26-2: Waste Flow Projections, Thousand Tonnes 

Waste Flow 

2015 

2020 

2025 

2030 

2035 

Generation 

Treatment 

27,962 

27,962 

29,901 

29,901 

31,426 

31,426 

33,029 

33,029 

34,714 

34,714 

The amount of waste generated by material is calculated using a specified waste 
composition. For each Member State there is the option to use either a ‘High Mineral 
Waste’ or ‘High Wood’ composition (for more details of the methodology used to estimate 
waste compositions please refer to Appendix 1).  

Our review of waste literature and data sources found no C&D waste composition data for 
Spain. We therefore proceeded to undertake a qualitative assessment of waste 
compositions in Spain and judged that a ‘High Mineral Waste’ composition would be most 
appropriate (Table 26-3). 

Table 26-3: C&D Waste Compositions for Modelling 

Compositional Set 

Wood 

Glass 

Metals 

Plastics  Gypsum 

Soil 

Mineral 
Waste 

Other 

High Mineral Waste 

3.3% 

0.1% 

1.5% 

0.9% 

1.4% 

37.0% 

51.4% 

4.5% 

26.1.2  Recycling and Backfill Projections 

The projected recycling and backfilling rates are key model inputs driving the overall results. 
To understand how these rates influences the results of the CBA we need to understand the 
change in the recycling and backfilling rates between the ‘Business as Usual’ and ‘More 
Ambitious’ scenarios. The key figures for the two scenarios are given in Table 26-4 and Table 
26-5. 

54 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
55 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

123 

 
 
 
                                                      
 
Table 26-4: Recycling Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

68.30% 

68.94% 

0.64% 

68.30% 

70.00% 

1.70% 

68.30% 

70.00% 

1.70% 

68.30% 

70.00% 

1.70% 

68.30% 

70.00% 

1.70% 

Table 26-5: Backfill Rate Projections 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Full Implementation (b) 

Difference (b-a) 

15.80% 

15.17% 

-0.64% 

15.80% 

14.10% 

-1.70% 

15.80% 

14.10% 

-1.70% 

15.80% 

14.10% 

-1.70% 

15.80% 

14.10% 

-1.70% 

26.1.3  Residual Waste Management 

In addition to the management of dry recycling, the management of residual waste has a 
significant impact on the overall costs and benefits. Table 26-6 and Table 26-7 show the 
proportion of C&D waste that is sent to incineration and landfill. The remainder is either 
recycled or backfilled.  

Table 26-6: Incineration Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

Table 26-7: Landfill Rate 

Scenario 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

More Ambitious (b) 

Difference (b-a) 

15.90% 

15.90% 

0.00% 

15.90% 

15.90% 

0.00% 

15.90% 

15.90% 

0.00% 

15.90% 

15.90% 

0.00% 

15.90% 

15.90% 

0.00% 

26.1.4  Summary of Waste Treatment Destinations 

The change in waste treatment destinations when moving from the ‘Business as Usual’ to 
the ‘More Ambitious’ scenarios are presented in Table 26-8.  

Table 26-8: Waste Treatment Destinations, Thousand Tonnes 

Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

Business as Usual (a) 

Recycling 

Backfill 

Incineration 

Landfill 

19,098 

20,422 

21,464 

22,559 

23,710 

4,419 

4,725 

4,966 

5,220 

5,486 

0 

0 

0 

0 

0 

4,445 

4,754 

4,996 

5,251 

5,519 

 
 
 
 
 
Scenario 

Treatment Type 

2015 

2020 

2025 

2030 

2035 

More Ambitious (b) 

Difference (b-a) 

Recycling 

Backfill 

Incineration 

Landfill 

Recycling 

Backfill 

Incineration 

Landfill 

19,276 

20,931 

21,998 

23,121 

24,300 

4,241 

4,217 

4,432 

4,658 

4,896 

0 

4,445 

178 

-178 

0 

0 

0 

4,754 

509 

-509 

0 

0 

0 

4,996 

535 

-535 

0 

0 

0 

5,251 

562 

-562 

0 

0 

0 

5,519 

590 

-590 

0 

0 

Figure 26-1 shows the overall change in recycling, backfilling, incineration, and landfill rates 
associated with a shift from the ‘Business as Usual’ to the ‘More Ambitious’ scenario. These 
figures show that the increase in recycling when moving towards 70% recycling in 2020 is 
offset by a decrease in backfilling. 

Figure 26-1: Business as Usual vs More Ambitious Scenario – Change in Final 
Management Destinations 

26.2 

Financial Costs 

The key waste collection and treatment assumptions used in the model are set out in 
Section 3 of Appendix 1. The calculated waste collection and treatment unit costs for each 
treatment type are summarised in Table 26-9. Note that these costs effectively include 
collection and sorting, and are quoted net of revenues generated from the sale of materials. 

28/05/2015 

125 

 
 
 
 
Table 26-9: Waste Collection and Treatment Unit Costs (2015 Real Term 
Prices), € per Tonne of Material Processed 

Waste Type 

Container 

Primary Treatment Type 

Unit Cost, € per Tonne 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Mixed Waste 

Wood 

Glass 

Metals 

Plastics  

Gypsum 

Soil 

Mineral Waste and Asphalt 

Skip 

Skip 

Skip 

Skip 

Building Bags 

660L bin 

240L bin 

Building Bags 

Building Bags 

Skip 

Skip 

Landfill 

Incineration 

Backfill 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

Recycling 

€ 33.96 

€ 33.96 

€ 33.46 

€ 32.46 

€ 41.82 

€ 22.16 

€ 11.13 

€ 37.05 

€ 33.62 

€ 24.69 

€ 24.83 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The change in collection and treatment costs 
of moving from the ‘Business as Usual’ to the ‘More Ambitious’ Scenario are presented in 
Table 26-10. These costs also take into account the revenue associated with the sale of 
recyclables. 

Table 26-10: Business as Usual vs More Ambitious Scenario – Change in 
Financial Costs, Thousand € (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Incineration 
to Recycling 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

-€ 747.21 

-€ 
1,022.39 
-€ 88.75 

-€ 
2,130.72 
-€ 
2,915.42 
-€ 253.08 

-€ 
2,239.41 
-€ 
3,064.13 
-€ 265.99 

-€ 
2,353.64 
-€ 
3,220.44 
-€ 279.56 

-€ 
2,473.70 
-€ 
3,384.71 
-€ 293.82 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 146.22 

€ 416.95 

€ 438.22 

€ 460.58 

€ 484.07 

-€ 0.98 

-€ 2.78 

-€ 2.93 

-€ 3.07 

-€ 3.23 

-€ 14.73 

-€ 42.01 

-€ 44.16 

-€ 46.41 

-€ 48.78 

€ 1.09 

€ 0.02 

€ 3.12 

€ 0.05 

€ 3.28 

€ 0.06 

€ 3.44 

€ 0.06 

€ 3.62 

€ 0.06 

€ 56.09 

€ 159.95 

€ 168.11 

€ 176.68 

€ 185.70 

Mineral Waste and Asphalt 

€ 85.47 

€ 243.73 

€ 256.16 

€ 269.23 

€ 282.96 

Other C&D 

€ 6.67 

€ 19.01 

€ 19.98 

€ 21.00 

€ 22.07 

 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Total 

-€ 1,579 

-€ 4,501 

-€ 4,731 

-€ 4,972 

-€ 5,226 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

26.3 

Environmental Costs 

The key environmental assumptions used in the model are set out in Section 2.2 of 
Appendix 1. The calculated external unit costs for a switch from landfill and incineration to 
recycling are summarised in Table 26-11. These costs reflect the combined impact of both 
the climate change impacts together with those impacts associated with other emissions to 
air such as NOx and PM. 

Table 26-11: Business as Usual vs More Ambitious Scenario – Change in 
External Unit Costs, € per Tonne of Material Treated (2015 Real Term Prices) 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Soil 

Mineral Waste and Asphalt 

Other C&D 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 7.32 

-€ 6.43 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 7.32 

-€ 6.43 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 7.32 

-€ 6.43 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 7.78 

-€ 6.59 

-€ 3.57 

-€ 3.57 

-€ 3.57 

€ 11.14 

-€ 7.77 

-€ 95.43 

-€ 95.43 

-€ 95.43 

-€ 103.99 

-€ 166.76 

-€ 89.26 

-€ 89.26 

-€ 89.26 

-€ 97.62 

-€ 158.95 

-€ 61.69 

-€ 71.38 

-€ 84.62 

-€ 102.43 

-€ 124.24 

-€ 4.91 

-€ 4.91 

-€ 4.91 

-€ 4.99 

-€ 5.52 

-€ 93.92 

-€ 93.92 

-€ 93.92 

-€ 102.39 

-€ 164.50 

-€ 51.13 

-€ 51.13 

-€ 51.13 

-€ 54.51 

-€ 79.33 

-€ 6.68 

-€ 8.50 

-€ 8.50 

-€ 8.50 

-€ 6.68 

-€ 8.50 

-€ 8.50 

-€ 8.50 

-€ 6.68 

-€ 8.50 

-€ 8.50 

-€ 8.50 

-€ 6.97 

-€ 8.57 

-€ 8.57 

-€ 8.57 

-€ 9.10 

-€ 9.10 

-€ 9.10 

-€ 9.10 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The greenhouse gas unit impacts for these same switches in treatment options are 
summarised in Table 26-12. 

Table 26-12: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Unit Impacts, Tonnes CO2 Equivalent per Tonne of Material 
Treated 

Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Wood 

Glass 

Metals  

0.15 

-0.05 

-2.85 

0.15 

-0.05 

-2.85 

0.15 

-0.05 

-2.85 

0.15 

-0.05 

-2.85 

0.15 

-0.05 

-2.85 

28/05/2015 

127 

 
 
 
Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Switch from 
Landfill to 
Recycling 

Mineral Waste and Asphalt 

Other C&D 

-2.79 

-0.52 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.79 

-0.52 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.79 

-0.52 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.79 

-0.52 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

-2.79 

-0.52 

-0.02 

-2.82 

-1.13 

-0.10 

-0.02 

-0.02 

-0.02 

Note: Positive values denote an increase in greenhouse gas emissions. 

The change in external costs of moving from the ‘Business as Usual’ to the ‘More Ambitious’ 
Scenario are presented in Table 26-13.   

Table 26-13: Business as Usual vs More Ambitious Scenario – Change in 
External Costs, Thousand € (2015 Real Term Prices) 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Backfill to 
Recycling 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Total 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

-€ 253.80 

-€ 352.97 

-€ 30.64 

-€ 723.72 
-€ 
1,006.52 
-€ 87.37 

-€ 760.63 
-€ 
1,057.87 
-€ 91.83 

-€ 799.43 

-€ 840.21 

-€ 1,111.83 

-€ 1,168.54 

-€ 96.51 

-€ 101.44 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 
Mineral Waste and 
Asphalt 
Other C&D 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 752.64 

-€ 0.32 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 
-€ 
2,483.26 
-€ 0.92 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 
-€ 
3,094.04 
-€ 0.97 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

€ 0.00 

-€ 3,936.06 

-€ 5,017.67 

-€ 1.04 

-€ 1.20 

-€ 73.51 

-€ 209.63 

-€ 220.32 

-€ 252.44 

-€ 426.27 

-€ 10.81 

-€ 30.84 

-€ 32.41 

-€ 36.32 

-€ 55.55 

-€ 2.14 

-€ 6.10 

-€ 6.41 

-€ 7.03 

-€ 9.65 

€ 43.23 

€ 123.28 

€ 129.57 

€ 137.34 

€ 153.25 

€ 66.91 

€ 190.80 

€ 200.53 

€ 212.55 

€ 237.17 

€ 5.22 

€ 14.88 

€ 15.64 

€ 16.58 

€ 18.50 

-€ 1,361 

-€ 4,219 

-€ 4,919 

-€ 5,874 

-€ 7,212 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

The change in greenhouse gas emissions of moving from the ‘Business as Usual’ to the 
‘More Ambitious’ Scenario are presented in Table 26-14. 

 
 
 
Table 26-14: Business as Usual vs More Ambitious Scenario – Change in 
Greenhouse Gas Impacts, Thousand Tonnes CO2 Equivalent 

 Material Source and Waste Type  

2015 

2020 

2025 

2030 

2035 

Switch from 
Incineration 
to Recycling 

Switch from 
Landfill to 
Recycling 

Wood 

Glass 

Metals  

Plastics  

Wood 

Glass 

Metals 

Plastics 

Gypsum 

Soil 

Mineral Waste and Asphalt 

Other C&D 

0.00 

0.00 

0.00 

0.00 

-6.35 

0.00 

-2.21 

-0.24 

-0.03 

0.12 

0.19 

0.01 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

0.00 

-18.12 

-19.04 

-20.02 

-21.04 

0.00 

-6.30 

-0.68 

-0.09 

0.35 

0.54 

0.04 

0.00 

-6.62 

-0.72 

-0.09 

0.37 

0.57 

0.04 

0.00 

-6.96 

-0.75 

-0.10 

0.39 

0.60 

0.05 

-0.01 

-7.32 

-0.79 

-0.10 

0.40 

0.63 

0.05 

Total 

-8.51 

-24.27 

-25.50 

-26.80 

-28.17 

Note: Positive values denote an increase in greenhouse gas emissions. 

26.4 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from the ‘Business as 
Usual’ to the ‘More Ambitious’ scenario are shown in Figure 26-2 and Table 26-15. From this 
it is clear that there is a net benefit to be gained from moving towards higher recycling rates 
(this is shown by the negative cost values). 

28/05/2015 

129 

 
 
Figure 26-2: Net Social Costs – Business as Usual vs More Ambitious Scenario 
(2015 Real Term Prices) 

Table 26-15: Net Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits, Million € 

2015 

2020 

2025 

2030 

2035 

Net Present Value 
(NPV), 2015 – 2035, 
Million € 

Environmental Externalities 

-€ 1.36 

-€ 4.22 

-€ 4.92 

-€ 5.87 

-€ 7.21 

Financial Costs (social metric) 

-€ 1.58 

-€ 4.50 

-€ 4.73 

Net Costs and Benefits 

-€ 2.94 

-€ 8.72 

-€ 9.65 

-€ 4.97 
-€ 
10.85 

-€ 5.23 
-€ 
12.44 

-€ 61.8 

-€ 58.1 

-€ 119.9 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society. 

 
 
 
 
27.0  Sweden 

According to Eurostat, the C&D recycling rate for Sweden was 79% in 2012.56,57 This rate is 
above the 70% recycling target specified by the ‘More Ambitious’ scenario and was 
therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

56 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
57 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

28/05/2015 

131 

 
 
 
                                                      
 
28.0  United Kingdom 

According to Eurostat, the C&D recycling rate for the United Kingdom was 91% in 2012.58,59 
This rate is above the 70% recycling target specified by the ‘More Ambitious’ scenario and 
was therefore held constant for future years in this model scenario. Accordingly, there is no 
change in final waste management destinations when moving from the ‘Business as Usual’ 
to ‘More Ambitious’ scenario and therefore no results to report. 

58 Eurostat (2015) Generation of Waste [env_wasgen], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wasgen&lang=en 
59 Eurostat (2015) Treatment of Waste [env_wastrt], Accessed 24th March 2015, 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_wastrt&lang=en 

 
 
                                                      
 
FURTHER DEVELOPMENT OF 
THE EUROPEAN REFERENCE 
MODEL ON WASTE 
GENERATION AND 
MANAGEMENT 

FINAL REPORT – APPENDIX 3: MEMBER 
STATE SUMMARY REPORTS 

Dr Dominic Hogg 

Thomas Vergunst 

Timothy Elliott 

Laurence Elliott 

Mark Corbin 

28th May 2015 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Report for Michel Sponar, DG Environment of the European Commission 

Prepared by Thomas Vergunst, Timothy Elliott, Laurence Elliott, Mark 
Corbin 

Approved by  

Dr Dominic Hogg 

(Project Director) 

Eunomia Research & Consulting Ltd 
37 Queen Square 
Bristol 
BS1 4QS 

United Kingdom 

Tel: +44 (0)117 9172250 
Fax: +44 (0)8717 142942 

Web: www.eunomia.co.uk 

Disclaimer 

Eunomia Research & Consulting has taken due care in the preparation of this report to 
ensure that all facts and analysis presented are as accurate as possible within the 
scope of the project. However no guarantee is provided in respect of the information 
presented, and Eunomia Research & Consulting is not responsible for decisions or 
actions taken on the basis of the content of this report. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

1.0 

2.0 

3.0 

4.0 

Introduction ....................................................................................................15 

Development of the European Reference Model on Municipal Waste Management
17 

Updates to the European Reference Model on Municipal Waste Management....19 

Approach to Collections Modelling ...................................................................21 

4.1  Baseline Collections System ........................................................................................... 21 

4.2  Moving to Higher Recycling Rates ................................................................................. 21 

4.3  Collection from Urban vs Rural Househols ................................................................... 23 

4.4  Revenues from the Sale of Recyclables ......................................................................... 24 

4.5 

Losses from Sorting and Reprocessing Facilities .......................................................... 26 

5.0 

Main Uncertainties Associated with the Model .................................................28 

5.1  Collection ......................................................................................................................... 28 

5.2 

Treatment ........................................................................................................................ 29 

5.3 

Externalities ..................................................................................................................... 29 

5.4  Prevention Impacts ......................................................................................................... 30 

5.5 

Summary.......................................................................................................................... 30 

6.0 

7.0 

Member State Data Tables ...............................................................................32 

Austria............................................................................................................36 

7.1  Waste Generation and Management Projections ........................................................ 37 

7.1.1  Waste Generation .................................................................................................... 38 

7.1.2  Recycling Projections ............................................................................................... 39 

7.1.3  Residual Waste Management ................................................................................. 40 

7.2  Change in Waste Collection Systems............................................................................. 42 

7.3 

Financial Costs ................................................................................................................. 42 

7.3.1 

Costs of Waste Collection ........................................................................................ 42 

7.3.2 

Costs of Waste Treatment ....................................................................................... 44 

7.3.3 

Total Financial Costs ................................................................................................ 45 

7.4 

Environmental Costs ....................................................................................................... 45 

7.5 

Summary of Costs and Benefits ..................................................................................... 48 

8.0 

Belgium ..........................................................................................................51 

8.1  Waste Generation and Management Projections ........................................................ 52 

8.1.1  Waste Generation .................................................................................................... 53 

iii 

 
 
 
8.1.2  Recycling Projections ............................................................................................... 54 

8.1.3  Residual Waste Management ................................................................................. 55 

8.2  Change in Waste Collection Systems............................................................................. 57 

8.3 

Financial Costs ................................................................................................................. 57 

8.3.1 

Costs of Waste Collection ........................................................................................ 57 

8.3.2 

Costs of Waste Treatment ....................................................................................... 59 

8.3.3 

Total Financial Costs ................................................................................................ 60 

8.4 

Environmental Costs ....................................................................................................... 60 

8.5 

Summary of Costs and Benefits ..................................................................................... 62 

9.0 

Bulgaria ..........................................................................................................66 

9.1  Waste Generation and Management Projections ........................................................ 67 

9.1.1  Waste Generation .................................................................................................... 68 

9.1.2  Recycling Projections ............................................................................................... 69 

9.1.3  Residual Waste Management ................................................................................. 71 

9.2  Change in Waste Collection Systems............................................................................. 72 

9.3 

Financial Costs ................................................................................................................. 73 

9.3.1 

Costs of Waste Collection ........................................................................................ 73 

9.3.2 

Costs of Waste Treatment ....................................................................................... 75 

9.3.3 

Total Financial Costs ................................................................................................ 75 

9.4 

Environmental Costs ....................................................................................................... 76 

9.5 

Summary of Costs and Benefits ..................................................................................... 78 

10.0 

Croatia............................................................................................................81 

10.1  Waste Generation and Management Projections .................................................... 82 

10.1.1  Waste Generation ................................................................................................ 83 

10.1.2 

Recycling Projections ............................................................................................ 84 

10.1.3 

Residual Waste Management ............................................................................. 86 

10.2 

Change in Waste Collection Systems ......................................................................... 87 

10.3 

Financial Costs ............................................................................................................. 88 

10.3.1 

Costs of Waste Collection..................................................................................... 88 

10.3.2 

Costs of Waste Treatment ................................................................................... 90 

10.3.3 

Total Financial Costs............................................................................................. 90 

10.4 

Environmental Costs ................................................................................................... 91 

10.5 

Summary of Costs and Benefits.................................................................................. 93 

11.0 

Cyprus ............................................................................................................96 

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11.1  Waste Generation and Management Projections .................................................... 97 

11.1.1  Waste Generation ................................................................................................ 98 

11.1.2 

Recycling Projections ............................................................................................ 99 

11.1.3 

Residual Waste Management ........................................................................... 101 

11.2 

Change in Waste Collection Systems ....................................................................... 102 

11.3 

Financial Costs ........................................................................................................... 103 

11.3.1 

Costs of Waste Collection................................................................................... 103 

11.3.2 

Costs of Waste Treatment ................................................................................. 104 

11.3.3 

Total Financial Costs........................................................................................... 105 

11.4 

Environmental Costs ................................................................................................. 106 

11.5 

Summary of Costs and Benefits................................................................................ 108 

12.0 

Czech Republic .............................................................................................. 111 

12.1  Waste Generation and Management Projections .................................................. 112 

12.1.1  Waste Generation .............................................................................................. 113 

12.1.2 

Recycling Projections .......................................................................................... 114 

12.1.3 

Residual Waste Management ........................................................................... 116 

12.2 

Change in Waste Collection Systems ....................................................................... 117 

12.3 

Financial Costs ........................................................................................................... 118 

12.3.1 

Costs of Waste Collection................................................................................... 118 

12.3.2 

Costs of Waste Treatment ................................................................................. 119 

12.3.3 

Total Financial Costs........................................................................................... 120 

12.4 

Environmental Costs ................................................................................................. 121 

12.5 

Summary of Costs and Benefits................................................................................ 123 

13.0 

Denmark ....................................................................................................... 126 

13.1  Waste Generation and Management Projections .................................................. 127 

13.1.1  Waste Generation .............................................................................................. 128 

13.1.2 

Recycling Projections .......................................................................................... 129 

13.1.3 

Residual Waste Management ........................................................................... 130 

13.2 

Change in Waste Collection Systems ....................................................................... 132 

13.3 

Financial Costs ........................................................................................................... 132 

13.3.1 

Costs of Waste Collection................................................................................... 132 

13.3.2 

Costs of Waste Treatment ................................................................................. 134 

13.3.3 

Total Financial Costs........................................................................................... 135 

13.4 

Environmental Costs ................................................................................................. 135 

v 

 
 
13.5 

Summary of Costs and Benefits................................................................................ 138 

14.0 

Estonia ......................................................................................................... 141 

14.1  Waste Generation and Management Projections .................................................. 142 

14.1.1  Waste Generation .............................................................................................. 143 

14.1.2 

Recycling Projections .......................................................................................... 144 

14.1.3 

Residual Waste Management ........................................................................... 146 

14.2 

Change in Waste Collection Systems ....................................................................... 147 

14.3 

Financial Costs ........................................................................................................... 148 

14.3.1 

Costs of Waste Collection................................................................................... 148 

14.3.2 

Costs of Waste Treatment ................................................................................. 149 

14.3.3 

Total Financial Costs........................................................................................... 150 

14.4 

Environmental Costs ................................................................................................. 151 

14.5 

Summary of Costs and Benefits................................................................................ 153 

15.0 

Finland ......................................................................................................... 156 

15.1  Waste Generation and Management Projections .................................................. 157 

15.1.1  Waste Generation .............................................................................................. 158 

15.1.2 

Recycling Projections .......................................................................................... 159 

15.1.3 

Residual Waste Management ........................................................................... 160 

15.2 

Change in Waste Collection Systems ....................................................................... 162 

15.3 

Financial Costs ........................................................................................................... 162 

15.3.1 

Costs of Waste Collection................................................................................... 162 

15.3.2 

Costs of Waste Treatment ................................................................................. 164 

15.3.3 

Total Financial Costs........................................................................................... 165 

15.4 

Environmental Costs ................................................................................................. 165 

15.5 

Summary of Costs and Benefits................................................................................ 168 

16.0 

France .......................................................................................................... 171 

16.1  Waste Generation and Management Projections .................................................. 172 

16.1.1  Waste Generation .............................................................................................. 173 

16.1.2 

Recycling Projections .......................................................................................... 174 

16.1.3 

Residual Waste Management ........................................................................... 176 

16.2 

Change in Waste Collection Systems ....................................................................... 177 

16.3 

Financial Costs ........................................................................................................... 178 

16.3.1 

Costs of Waste Collection................................................................................... 178 

16.3.2 

Costs of Waste Treatment ................................................................................. 179 

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16.3.3 

Total Financial Costs........................................................................................... 180 

16.4 

Environmental Costs ................................................................................................. 181 

16.5 

Summary of Costs and Benefits................................................................................ 183 

17.0 

Germany ....................................................................................................... 186 

17.1  Waste Generation and Management Projections .................................................. 187 

17.1.1  Waste Generation .............................................................................................. 188 

17.1.2 

Recycling Projections .......................................................................................... 189 

17.1.3 

Residual Waste Management ........................................................................... 190 

17.2 

Change in Waste Collection Systems ....................................................................... 192 

17.3 

Financial Costs ........................................................................................................... 192 

17.3.1 

Costs of Waste Collection................................................................................... 192 

17.3.2 

Costs of Waste Treatment ................................................................................. 194 

17.3.3 

Total Financial Costs........................................................................................... 195 

17.4 

Environmental Costs ................................................................................................. 195 

17.5 

Summary of Costs and Benefits................................................................................ 198 

18.0 

Greece .......................................................................................................... 201 

18.1  Waste Generation and Management Projections .................................................. 202 

18.1.1  Waste Generation .............................................................................................. 203 

18.1.2 

Recycling Projections .......................................................................................... 204 

18.1.3 

Residual Waste Management ........................................................................... 206 

18.2 

Change in Waste Collection Systems ....................................................................... 207 

18.3 

Financial Costs ........................................................................................................... 208 

18.3.1 

Costs of Waste Collection................................................................................... 208 

18.3.2 

Costs of Waste Treatment ................................................................................. 210 

18.3.3 

Total Financial Costs........................................................................................... 210 

18.4 

Environmental Costs ................................................................................................. 211 

18.5 

Summary of Costs and Benefits................................................................................ 213 

19.0 

Hungary ........................................................................................................ 216 

19.1  Waste Generation and Management Projections .................................................. 217 

19.1.1  Waste Generation .............................................................................................. 218 

19.1.2 

Recycling Projections .......................................................................................... 219 

19.1.3 

Residual Waste Management ........................................................................... 221 

19.2 

Change in Waste Collection Systems ....................................................................... 222 

19.3 

Financial Costs ........................................................................................................... 223 

vii 

 
 
19.3.1 

Costs of Waste Collection................................................................................... 223 

19.3.2 

Costs of Waste Treatment ................................................................................. 225 

19.3.3 

Total Financial Costs........................................................................................... 225 

19.4 

Environmental Costs ................................................................................................. 226 

19.5 

Summary of Costs and Benefits................................................................................ 228 

20.0 

Ireland .......................................................................................................... 231 

20.1  Waste Generation and Management Projections .................................................. 232 

20.1.1  Waste Generation .............................................................................................. 233 

20.1.2 

Recycling Projections .......................................................................................... 234 

20.1.3 

Residual Waste Management ........................................................................... 235 

20.2 

Change in Waste Collection Systems ....................................................................... 237 

20.3 

Financial Costs ........................................................................................................... 237 

20.3.1 

Costs of Waste Collection................................................................................... 237 

20.3.2 

Costs of Waste Treatment ................................................................................. 239 

20.3.3 

Total Financial Costs........................................................................................... 240 

20.4 

Environmental Costs ................................................................................................. 240 

20.5 

Summary of Costs and Benefits................................................................................ 243 

21.0 

Italy .............................................................................................................. 246 

21.1  Waste Generation and Management Projections .................................................. 247 

21.1.1  Waste Generation .............................................................................................. 248 

21.1.2 

Recycling Projections .......................................................................................... 249 

21.1.3 

Residual Waste Management ........................................................................... 251 

21.2 

Change in Waste Collection Systems ....................................................................... 252 

21.3 

Financial Costs ........................................................................................................... 253 

21.3.1 

Costs of Waste Collection................................................................................... 253 

21.3.2 

Costs of Waste Treatment ................................................................................. 254 

21.3.3 

Total Financial Costs........................................................................................... 255 

21.4 

Environmental Costs ................................................................................................. 256 

21.5 

Summary of Costs and Benefits................................................................................ 258 

22.0 

Latvia ........................................................................................................... 261 

22.1  Waste Generation and Management Projections .................................................. 262 

22.1.1  Waste Generation .............................................................................................. 263 

22.1.2 

Recycling Projections .......................................................................................... 264 

22.1.3 

Residual Waste Management ........................................................................... 266 

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22.2 

Change in Waste Collection Systems ....................................................................... 267 

22.3 

Financial Costs ........................................................................................................... 267 

22.3.1 

Costs of Waste Collection................................................................................... 267 

22.3.2 

Costs of Waste Treatment ................................................................................. 269 

22.3.3 

Total Financial Costs........................................................................................... 270 

22.4 

Environmental Costs ................................................................................................. 270 

22.5 

Summary of Costs and Benefits................................................................................ 273 

23.0 

Lithuania....................................................................................................... 276 

23.1  Waste Generation and Management Projections .................................................. 277 

23.1.1  Waste Generation .............................................................................................. 278 

23.1.2 

Recycling Projections .......................................................................................... 279 

23.1.3 

Residual Waste Management ........................................................................... 281 

23.2 

Change in Waste Collection Systems ....................................................................... 282 

23.3 

Financial Costs ........................................................................................................... 283 

23.3.1 

Costs of Waste Collection................................................................................... 283 

23.3.2 

Costs of Waste Treatment ................................................................................. 284 

23.3.3 

Total Financial Costs........................................................................................... 285 

23.4 

Environmental Costs ................................................................................................. 286 

23.5 

Summary of Costs and Benefits................................................................................ 288 

24.0 

Luxembourg .................................................................................................. 291 

24.1  Waste Generation and Management Projections .................................................. 292 

24.1.1  Waste Generation .............................................................................................. 293 

24.1.2 

Recycling Projections .......................................................................................... 294 

24.1.3 

Residual Waste Management ........................................................................... 295 

24.2 

Change in Waste Collection Systems ....................................................................... 297 

24.3 

Financial Costs ........................................................................................................... 297 

24.3.1 

Costs of Waste Collection................................................................................... 297 

24.3.2 

Costs of Waste Treatment ................................................................................. 299 

24.3.3 

Total Financial Costs........................................................................................... 300 

24.4 

Environmental Costs ................................................................................................. 300 

24.5 

Summary of Costs and Benefits................................................................................ 303 

25.0  Malta............................................................................................................ 306 

25.1  Waste Generation and Management Projections .................................................. 307 

25.1.1  Waste Generation .............................................................................................. 308 

ix 

 
 
25.1.2 

Recycling Projections .......................................................................................... 309 

25.1.3 

Residual Waste Management ........................................................................... 311 

25.2 

Change in Waste Collection Systems ....................................................................... 312 

25.3 

Financial Costs ........................................................................................................... 313 

25.3.1 

Costs of Waste Collection................................................................................... 313 

25.3.2 

Costs of Waste Treatment ................................................................................. 314 

25.3.3 

Total Financial Costs........................................................................................... 315 

25.4 

Environmental Costs ................................................................................................. 316 

25.5 

Summary of Costs and Benefits................................................................................ 318 

26.0  Netherlands .................................................................................................. 321 

26.1  Waste Generation and Management Projections .................................................. 322 

26.1.1  Waste Generation .............................................................................................. 323 

26.1.2 

Recycling Projections .......................................................................................... 324 

26.1.3 

Residual Waste Management ........................................................................... 325 

26.2 

Change in Waste Collection Systems ....................................................................... 327 

26.3 

Financial Costs ........................................................................................................... 327 

26.3.1 

Costs of Waste Collection................................................................................... 327 

26.3.2 

Costs of Waste Treatment ................................................................................. 329 

26.3.3 

Total Financial Costs........................................................................................... 330 

26.4 

Environmental Costs ................................................................................................. 330 

26.5 

Summary of Costs and Benefits................................................................................ 333 

27.0 

Poland .......................................................................................................... 336 

27.1  Waste Generation and Management Projections .................................................. 337 

27.1.1  Waste Generation .............................................................................................. 338 

27.1.2 

Recycling Projections .......................................................................................... 339 

27.1.3 

Residual Waste Management ........................................................................... 341 

27.2 

Change in Waste Collection Systems ....................................................................... 342 

27.3 

Financial Costs ........................................................................................................... 343 

27.3.1 

Costs of Waste Collection................................................................................... 343 

27.3.2 

Costs of Waste Treatment ................................................................................. 344 

27.3.3 

Total Financial Costs........................................................................................... 345 

27.4 

Environmental Costs ................................................................................................. 346 

27.5 

Summary of Costs and Benefits................................................................................ 348 

28.0 

Portugal ........................................................................................................ 351 

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28.1  Waste Generation and Management Projections .................................................. 352 

28.1.1  Waste Generation .............................................................................................. 353 

28.1.2 

Recycling Projections .......................................................................................... 354 

28.1.3 

Residual Waste Management ........................................................................... 356 

28.2 

Change in Waste Collection Systems ....................................................................... 357 

28.3 

Financial Costs ........................................................................................................... 358 

28.3.1 

Costs of Waste Collection................................................................................... 358 

28.3.2 

Costs of Waste Treatment ................................................................................. 359 

28.3.3 

Total Financial Costs........................................................................................... 360 

28.4 

Environmental Costs ................................................................................................. 361 

28.5 

Summary of Costs and Benefits................................................................................ 363 

29.0 

Romania ....................................................................................................... 366 

29.1  Waste Generation and Management Projections .................................................. 367 

29.1.1  Waste Generation .............................................................................................. 368 

29.1.2 

Recycling Projections .......................................................................................... 370 

29.1.3 

Residual Waste Management ........................................................................... 371 

29.2 

Change in Waste Collection Systems ....................................................................... 373 

29.3 

Financial Costs ........................................................................................................... 373 

29.3.1 

Costs of Waste Collection................................................................................... 373 

29.3.2 

Costs of Waste Treatment ................................................................................. 375 

29.3.3 

Total Financial Costs........................................................................................... 376 

29.4 

Environmental Costs ................................................................................................. 376 

29.5 

Summary of Costs and Benefits................................................................................ 379 

30.0 

Slovakia ........................................................................................................ 382 

30.1  Waste Generation and Management Projections .................................................. 383 

30.1.1  Waste Generation .............................................................................................. 384 

30.1.2 

Recycling Projections .......................................................................................... 385 

30.1.3 

Residual Waste Management ........................................................................... 387 

30.2 

Change in Waste Collection Systems ....................................................................... 388 

30.3 

Financial Costs ........................................................................................................... 389 

30.3.1 

Costs of Waste Collection................................................................................... 389 

30.3.2 

Costs of Waste Treatment ................................................................................. 390 

30.3.3 

Total Financial Costs........................................................................................... 391 

30.4 

Environmental Costs ................................................................................................. 392 

xi 

 
 
30.5 

Summary of Costs and Benefits................................................................................ 394 

31.0 

Slovenia ........................................................................................................ 397 

31.1  Waste Generation and Management Projections .................................................. 398 

31.1.1  Waste Generation .............................................................................................. 399 

31.1.2 

Recycling Projections .......................................................................................... 400 

31.1.3 

Residual Waste Management ........................................................................... 401 

31.2 

Change in Waste Collection Systems ....................................................................... 403 

31.3 

Financial Costs ........................................................................................................... 403 

31.3.1 

Costs of Waste Collection................................................................................... 403 

31.3.2 

Costs of Waste Treatment ................................................................................. 405 

31.3.3 

Total Financial Costs........................................................................................... 406 

31.4 

Environmental Costs ................................................................................................. 406 

31.5 

Summary of Costs and Benefits................................................................................ 409 

32.0 

Spain ............................................................................................................ 412 

32.1  Waste Generation and Management Projections .................................................. 413 

32.1.1  Waste Generation .............................................................................................. 414 

32.1.2 

Recycling Projections .......................................................................................... 415 

32.1.3 

Residual Waste Management ........................................................................... 417 

32.2 

Change in Waste Collection Systems ....................................................................... 418 

32.3 

Financial Costs ........................................................................................................... 419 

32.3.1 

Costs of Waste Collection................................................................................... 419 

32.3.2 

Costs of Waste Treatment ................................................................................. 420 

32.3.3 

Total Financial Costs........................................................................................... 421 

32.4 

Environmental Costs ................................................................................................. 421 

32.5 

Summary of Costs and Benefits................................................................................ 424 

33.0 

Sweden......................................................................................................... 427 

33.1  Waste Generation and Management Projections .................................................. 428 

33.1.1  Waste Generation .............................................................................................. 429 

33.1.2 

Recycling Projections .......................................................................................... 430 

33.1.3 

Residual Waste Management ........................................................................... 431 

33.2 

Change in Waste Collection Systems ....................................................................... 433 

33.3 

Financial Costs ........................................................................................................... 433 

33.3.1 

Costs of Waste Collection................................................................................... 433 

33.3.2 

Costs of Waste Treatment ................................................................................. 435 

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33.3.3 

Total Financial Costs........................................................................................... 436 

33.4 

Environmental Costs ................................................................................................. 436 

33.5 

Summary of Costs and Benefits................................................................................ 439 

34.0 

United Kingdom ............................................................................................ 442 

34.1  Waste Generation and Management Projections .................................................. 443 

34.1.1  Waste Generation .............................................................................................. 444 

34.1.2 

Recycling Projections .......................................................................................... 445 

34.1.3 

Residual Waste Management ........................................................................... 447 

34.2 

Change in Waste Collection Systems ....................................................................... 448 

34.3 

Financial Costs ........................................................................................................... 448 

34.3.1 

Costs of Waste Collection................................................................................... 448 

34.3.2 

Costs of Waste Treatment ................................................................................. 450 

34.3.3 

Total Financial Costs........................................................................................... 451 

34.4 

Environmental Costs ................................................................................................. 451 

34.5 

Summary of Costs and Benefits................................................................................ 454 

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1.0 

Introduction 

Eunomia Research & Consulting (Eunomia) has been commissioned by DG Environment of 
the European Commission to, among other things, further develop the European Reference 
Model on Municipal Waste Management. This project, entitled ‘Further Development of the 
European Reference Model on Waste Generation and Management’, is multifaceted and 
builds on previous work undertaken by Eunomia under the following two contracts: 

 
 

‘Development of a Modelling Tool on Waste Generation and Management’;1 and 
‘Impact Assessment on Options Reviewing Targets in the Waste Framework 
Directive’.2 

These projects have all been delivered under Eunomia’s framework contract with the 
European Commission on ‘Technological, Socio-Economic and Cost-Benefit Assessments 
Related to the Implementation and Further Development of EU Waste Legislation’. As noted 
in Box 1 the reports emerging from the contracts listed above provide an important context 
for this work and should be referred to for additional information and details about the 
structure and function of the waste model and the analysis undertaken as part of the 
targets review project.  

Box 1: Contextualising this Appendix 

In order to fully contextualise this appendix readers are encouraged to read the following 
documents which outline the work which was undertaken by Eunomia in supporting the 
development of the Impact Assessment which reviewed the European waste management targets: 

  Documentation accompanying the Targets Review Project – Eunomia Research & 

Consulting, Copenhagen Resource Institute, and Öko-Institut (2014) Impact Assessment on 
Options Reviewing Targets in the Waste Framework Directive, Landfill Directive and 
Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20
report.pdf 

  Technical documentation accompanying the European Reference Model on Municipal 

Waste Management – Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment and European Environment 
Agency, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

1 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool 
on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
2 Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-Institut (2014) Impact Assessment 
on Options Reviewing Targets in the Waste Framework Directive, Landfill Directive and Packaging and 
Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

15 

 
                                                   
 
The first document presents the rationale for developing the various options which were ultimately 
included in the Impact Assessment and summarises the costs and benefits of these options. The cost 
benefit analysis was undertaken using the European Reference Model on Municipal Waste 
Management which Eunomia developed in parallel to the Targets Review Project – the underlying 
assumptions and structure of this model are presented in the second document presented above. 
Throughout this appendix reference will be made to these two documents to signpost where 
additional information can be obtained. 

This appendix is intended to collate the most important country specific information and 
data which has been used in the European Reference Model on Municipal Waste 
Management (referred to from hereon as the ‘Municipal Waste Model’). An earlier version 
of the model was used to undertake the cost benefit analysis which was undertaken as part 
of the Impact Assessment which accompanied the proposal for reviewing the European 
waste management targets.3 As suggested by the title of this contract, it has been aimed at 
further developing and updating the model in a number of ways (including the development 
of a user interface to make the model more accessible to general users). 

Before presenting the country specific information this appendix covers a number of 
important overarching aspects that should be read and born in mind before reading the 
country specific sections. This appendix is structured as follows: 

  Section 2.0 - this section explains the process behind how the Municipal Waste 

Model was developed with direct input from Member States. 

  Section 3.0 – as noted above the Municipal Waste Model was further developed as 
part of this contract. This section outlines the key changes that have been made to 
the model. 

  Section 4.0 – given the complex nature of collections modelling, and the clear 

interest in this area of the mode since the publication of the results of the Impact 
Assessment, this section provides a broad overview of how the model accounts for 
the collection of municipal solid waste.  

  Section 5.0 – this section sets out the main uncertainties associated with the 

Municipal Waste Model which are important to bear in mind when considering the 
results that are presented in this appendix. 

  Section 6.0 – this section introduces the Member State Data Tables which 
accompany this Appendix and are intended to provide a repository of key 
assumptions and data relating to the analysis undertaken as part of this contract. 
  Section 7.0 to Section 34.0– these sections individually cover all 28 Member States 
and provide an outline of some of the specific information and data that has been 
used in Municipal Waste Model.       

3 European Commission (2014) Impact Assessment Accompanying the Document: Proposal for Reviewing the 
European Waste Management Targets, July 2014, http://ec.europa.eu/environment/waste/target_review.htm 

 
 
 
 
                                                   
 
2.0  Development of the European Reference 

Model on Municipal Waste Management 

The development of the Municipal Waste Model followed a number of steps which built on 
previous work and consulted with Member States to obtain valid input data. In essence, the 
steps taken within this work involved: 

  Reviewing the original EEA waste model; 
  Developing a new model;  
  Developing technical documentation for the new model; 
  Peer reviewing the technical documentation; 
  Consultations with Member States and non-Member State stakeholders to gain input 

data for the model; 

Input baseline data (including details on collection and treatment systems);  

 
  Develop and document baseline future projections; and 
  Model policy scenarios as part of the Commission’s Impact Assessment of the review 

of European waste management targets. 

As part of this process, relevant officials in all Member States were identified and sent a 
detailed questionnaire which requested country specific information which was required for 
input into the model. These questionnaires were sent out prior to Member States being 
visited in person to gather further information and to better understand the missing data 
gaps in the questionnaires which had been returned prior to these face-to-face meetings. 
Nineteen Member States were visited by members of the project team and these visits 
helped to develop a much more detailed view of current performance and future plans with 
respect to waste management.4  The countries which were not visited were felt to already 
be the better performers in terms of waste management and a substantial amount of 
information and data is already publically available; thus, information on these countries 
was gathered via the country questionnaire that was sent out combined with publically 
available sources of information.  

Under a separate contract with the EEA the Copenhagen Resource Institute (CRI) developed 
a waste model which preceded the Municipal Waste Model. Under this contract CRI 
consulted relevant stakeholders and aimed to populate their model with relevant Member 
State data. Some of this information was fed into the Municipal Waste Model which CRI also 
helped to develop.       

Industry was consulted via an online consultation which was hosted on the project’s official 
website. This consultation sought to obtain further information from stakeholders on: waste 

4 The following Member States were visited: Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Finland, France, 
Greece, Hungary, Italy, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Slovakia, Spain, and Sweden. Six of 
these countries were visited by the European Topic Centre on Sustainable Consumption and Production 
(ETC/SCP) on behalf of the European Environment Agency (EEA): Finland, France, Poland, Portugal, Spain, and 
Sweden. 

28/05/2015 

17 

 
                                                   
 
composition; collection systems operated in Member States and collection costs; and 
treatment system costs. 

These sources of information were used as sources of input data for the model which had 
been developed by the project team.  

The key technical documentation describing the approaches used within the model was 
subject to peer review – notably the financial modelling was peer reviewed by Scuola 
Agraria del Parco di Monza, and the environmental modelling by BIO Intelligence Service. 

 
 
3.0  Updates to the European Reference 
Model on Municipal Waste Management 

Under Eunomia’s existing contract with the Commission the Municipal Waste Model has 
been updated in a number of ways. The key changes are summarised in Table 3-1 and 
discussed in Section 3.2 of the main report. It is important to note that the updated model 
has been used to produce the results which are presented in the country summary reports 
below. We therefore also summarise in the table below how the individual changes will 
have altered the results since the model was used to run the scenarios for the Impact 
Assessment on the review of waste management targets.  

Table 3-1: Summary of Key Changes to the Municipal Waste Model  

Key Changes to the Municipal Waste Model 

The assumed composition of MSW has been updated for 
Lithuania because the country assumed that scrap metal 
was included in the municipal waste stream. The metal 
content of the waste stream was therefore very high and 
skewing the results.  .  

Changed datasets used for the labour cost ratios following 
comments from the EEA – harmonised datasets in the 
model using the hourly rate data from Eurostat, rather 
than mean net annual earnings.5  

Switched from the EU28 deflators to country specific 
deflators which are used to adjust some of the landfill and 
other taxes. 

All costs have been updated to 2015 real terms prices 
based on country specific deflators. 

Adjusted employment intensity factors in light of new 
information.  
The original model included a ‘goal seek’ function to pin 
Member State recycling and landfilling rates to the 
recycling target /landfill diversion target which had been 
set as part of the scenarios being modelled. This goal seek 
function was accurate to within ±1%. The functionality 
has been improved so that the model does not step by % 
point increments, and therefore is more accurate. 

Impact on the Results/Outputs Relative to the 
Version of the Model used for the Impact 
Assessment  

This appears to have had a very minimal effect on 
the results.  

The labour cost ratios will have changed for all 
Member States marginally affecting the labour 
costs in treatment plants and in waste collection 
services. This appears to have had a minimal 
effect on the results. 

Very slight changes to costs calculated. 

The outputs of both the financial and 
environmental modules will now be slightly 
different as the deflators have been updated. This 
change affects the magnitude of the results. As 
the value of money increases over time, moving 
from 2013 to 2015 prices will increase the costs 
or benefits, depending on the outcomes of the 
scenarios. 
Slight changes in the employment impacts of 
individual scenarios. 

This change will reduce the generation of 
anomalous results for Member States who are 
already very close to achieving the target 
recycling rate set out in a given policy scenario. 
For some countries the results will have changed 
by up to 1%. 

5 Eurostat: Labour cost levels [lc_lci_lev], 
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lc_lci_lev&lang=en 

28/05/2015 

19 

 
                                                   
 
Key Changes to the Municipal Waste Model 

Some aspects of the collections module have been 
updated to account more accurately for differences in 
collecting materials between a shared service (i.e. flats) 
and individual houses (i.e. door-to-door).    

The approach to calculating the cost of operation civic 
amenity sites (container parks) has been improved. 
Instead of calculating a single per household cost, the 
model now calculates the following element separately: 
1) investment costs, 2) labour costs and 3) other 
operational costs per tonne of throughput. 
The calculation method used to calculate Member State 
recycling rates for the 50% recycling target was updated 
for Denmark and the Netherlands. This was updated in 
light of new information that was made available to the 
European Commission (Denmark are now using method 1 
and the Netherlands are using method 2). 

Impact on the Results/Outputs Relative to the 
Version of the Model used for the Impact 
Assessment  

The extent of the change varies from country to 
country, depending on the proportion of the 
housing stock which is made up of buildings with 
more than 10 households each, and therefore 
utilise shared collection services. This change 
limits the capture from shared properties. The 
overall effect has been to increase the costs of 
waste collection.  

The overall effect had been to increase the costs 
of waste management.  

This will likely have had a very minor impact on 
the results.  

 
 
 
4.0  Approach to Collections Modelling 

The approach to collections modelling is outlined in detail in Appendix 5 of the technical 
documentation which accompanies the Municipal Waste Model and this appendix should be 
read alongside this section in order to gain a full understanding of the information 
presented below.6 It is important to note that no ‘one system’ is assumed to be used; 
instead, the model assumes that different systems are adopted over time as the 
requirement to reach higher recycling rates is triggered progressively.  

4.1 

Baseline Collections System 

The Collection Cost Module provides two core functions for the European Reference Model. 
In the first instance it allows current collection systems for any country to be defined in the 
model, and for the associated collection costs to be calculated. It then allows the user to 
consider what changes to collection systems might be required if ambition for recycling is to 
change, and what would be the associated costs of service change. 

A broad categorisation of collection system types operated within Member States can be 
given as follows: 

  Door-to-door (D2D) collections; 

  Bring sites; and 

  Civic amenity (CA) sites (sometimes also referred to as recycling centres). 

The collection cost model covers each of these collection system types, all of which may 
collect a range of recyclables, organic wastes, or mixed residual waste. The resource 
requirement for the collection operations (numbers of vehicles, containers, staff etc.) are 
calculated by the model. These resource requirements provide the basis for calculating the 
cost of collection for the currently operated collection systems.   

4.2 

Moving to Higher Recycling Rates 

Collection system costs for future years relate to the recycling rate to be achieved in the 
respective year. The model automatically moves a country from one collection system to 
another, depending on the recycling rate to be achieved. The costs of the mix of collection 
systems to be operated in future years are thereby calculated. This gives a profile of 
collection costs for each Member State as collection systems may evolve over time to satisfy 
future recycling ambitions. 

The model has five recycling collection system ‘groups’/‘typologies’ loaded within it and as 
recycling rates increase Member States are assumed to transition through these typologies 

6 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool 
on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

21 

 
                                                   
 
depending on the assumed future recycling rate that has been set. The recycling systems 
included in the model are defined as follows: 

  Group 1: Basic collection systems + some CA; 

  Group 2: More dense bring plus CA; 

  Group 3: Kerbside dry focussed; 

  Group 4: Kerbside dry and biowaste focussed without pay-as-you-throw (PAYT); and 

  Group 5: Kerbside dry and biowaste focussed including PAYT. 

These collection systems range from basic low performing services (group 1), through to 
advanced high recycling systems (group 5). In essence, the different collection system 
groups allow the model to calculate the cost of different services typologies to be calculated 
and apply these as Member States transition to higher recycling rates. The specific 
definitions for each collection system are presented in Table 4-1. 

Table 4-1: System Definitions for Future Year Modelled Groups of Collection 
Systems  

System Definitions 

Bring site 

Door to 
Door Dry 

Materials 

Density (no. 
households 
per site) 

Materials 

Frequency 

Door to Door organic 
Door to Door residual 
(non-flats) 

CA sites 

Group of Collection Systems 
Group 3 

Group 2 

Group 4 

Group 5 

Paper and cardboard; textiles glass; metals; plastics; mixed 
residual waste for flats. 

Group 1 
Paper and 
cardboard; 
glass; metals; 
plastics; mixed 
residual waste 
for flats. 

400 

200 

400 (500 for textiles) 

- 

- 

- 

- 

- 

Paper and cardboard, glass, 
metals, plastics and textiles 
Fortnightly 

Food weekly; garden fortnightly 

Weekly 

Fortnightly 

Fortnightly 
PAYT 

Standard with recycling, 
organic and residual waste 

Advanced with recycling, organic and residual 
waste 

The mix of collection systems is a function of the overall recycling rate and set through a 
range of assumptions regarding the likely roll-out of services across a country over a period 
of time. The approach is represented visually in Figure 4-1. The following points describe 
some key stages to exemplify the approach: 

  At 10% recycling the county has a 100% coverage of group 1 collection systems (i.e. 

basic bring with some CA sites); 

  At 25% recycling the country has an equal mix of basic and more dense bring 

systems; 

 
 
  By 37% recycling most of the bring systems have been replaced by door-to-door 

services operating on a fortnightly basis, but with some on a weekly and with some 
biowaste collection (a mix of type 3 and 4); 

  At 45% recycling some municipalities implement PAYT schemes in order to maintain 

the increase in recycling rates; and 

  By around 70% recycling most (75%) of household have switched from standard 

door-to-door services to PAYT. 

The progression from one system type to another was set based upon expert experience 
regarding the roll-out of different collection systems in different Member States. There is of 
course some subjectivity in this approach, but it is considered pragmatic and realistic.  

Figure 4-1: Change in Mix of System Types by Performance (Overall Recycling 
Rate) 

Note that the higher recycling rates are only achieved with a significant switch in collection 
systems to PAYT schemes. However, it should also be highlighted that the progression from 
group 1 to group 5 collection systems does not have to be linear. In fact there are likely to 
be cost savings through ‘leap frogging’ the intermediate systems from bring directly to door-
to-door PAYT services. 

The costs of additional communication associated with higher recycling targets have been 
included in the modelling. These increase as recycling rates increase at levels of an 
additional €1 per household per annum for achieving 50% recycling, €2 per household per 
annum for 60%, and €31 per household per annum for 70% recycling. 

4.3 

Collection from Urban vs Rural Househols 

The model makes assumptions which determine the number of households which can be 
served by a given vehicle. These are likely to vary from place to place. The model seeks to 

28/05/2015 

23 

0%10%20%30%40%50%60%70%80%90%100%01020252937455462697588100Coverage of System Type, % of householdsOverall Recycling Rate, Percentage PointsChange in Mix of System Types by PerformanceGroup of systems 1: Basic collection systems + some CAGroup of systems 2: More dense bring plus CAGroup of systems 3: Kerbside bio focussedGroup of systems 4: Kerbside dry+bio but not PAYTGroup of systems 5: Kerbside dry+bio including PAYT 
 
 
deal with this through setting different parameters for urban, suburban and rural 
households.  

Fundamental specifications, operational assumptions and performance data for the 
modelling of collection vehicles is given in Table 4-2. Much of this information is based on 
insight gained though Eunomia’s extensive experience modelling numerous kerbside 
collection systems in the UK. The efficiencies of the vehicles in terms of fuel consumption 
are likely to vary based on the distance between collections, the speed limits in place and 
with regard to how urban - and hence exposed to traffic congestion - certain regions are. 
Since these nuances are difficult to quantify in a model of this kind, the application of known 
values for one Member State across the others is suggested to be a reasonable compromise. 

Table 4-2: Collection Vehicle Assumptions 

Vehicle Type 

Capaci-
ty (m3) 

Fuel consumption (km/litre) 
Bring site 
Kerbside 

Cost  
(€, Ex VAT) 

32 Tonne RCV 
26 Tonne RCV 
26 Tonne RCV 
Split-back 
12 Tonne RCV 
12 Tonne Stillage 
Kerbsider 
26 Tonne RCV - 
PAYT 
12 Tonne RCV - 
PAYT 
7.5 Tonne food 
vehicle 
7.5 Tonne food 
vehicle UK 
Igloo Loader (top 
box with pen 
collection) 
26 Tonne side-
loader 
4 compartment 
back-loading 
vehicle 

23 
23 

23 

10 
30 
25 

23 

10 

9 

9 

20 

25 

21 

Urban 

Rural  Urban 

Rural 

1.3 
1.3 

1.3 

1.7 
3.4 
2.6 

1.3 

1.7 

2.1 

3.4 

1.9 
1.9 

1.9 

2.6 
5.1 
3.8 

1.9 

2.6 

3.2 

5.1 

1.5 
1.5 

1.5 

2.0 
4.1 
3.1 

1.5 

2.0 

2.6 

4.1 

2.3 
2.3 

2.3 

3.1 
6.1 
4.6 

2.3 

3.1 

3.8 

6.1 

€ 175,000 
€ 159,697 

€ 174,697 

€ 135,000 
€ 94,635 
€ 100,000 

€ 171,526 

€ 146,829 

€ 55,000 

€ 94,635 

0.0 

0.0 

1.5 

2.3 

€ 130,000 

0.0 

0.0 

1.5 

2.3 

€ 170,000 

1.3 

0.0 

1.5 

0.0 

€ 220,000 

Staff Per Vehicle 

Driver
s 

Crew 

1 
1 

1 

1 
1 
1 

1 

1 

1 

1 

1 

1 

1 

2 
2 

2 

1 
1.5 
1.5 

1 

1 

0 

1 

1 

0 

Sup-
er- 
visors 
0.1 
0.1 

0.1 

0.1 
0.1 
0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

0.1 

4.4 

Revenues from the Sale of Recyclables 

The modelled revenues generated on material sent for recycling are listed in Table 4-3. As 
noted in Table 3-1, these revenues have been updated as part of this contract. The material 
revenues used in the earlier version of the model was updated to account for changing 
market conditions over recent years. However, given that the revenues are projected over 
the period to 2035 it is very difficult (if not impossible) to predict how they may change over 
this period. For this reason, a simplified assumption has been taken which assumes that 
revenues will remain constant. The sensitivity tests conducted as part of this contract allows 
one to determine how changes in these values may impact on the final outputs of the 

 
  
 
model. The material revenues in the model have now been updated using WRAP and 
MRW’s latest Material Pricing Report for the UK.7 This report provides average weekly 
prices for a range of secondary materials and is a widely cited source of market data in the 
UK. Given the European wide trade in secondary materials these figures are believed to be 
reflective of the European market and therefore suitable for inclusion in the Municipal 
Waste Model. The following approach was taken: 

1)  The average material prices were calculated for each material over a two year period 

(i.e. June 2013 to June 2015); 8 

2)  The average Euro / pound sterling exchange rate was calculated for the same period 

using monthly average exchange rates from Eurostat (€1 = £0.800288);9 

3)  The average material prices are shown in Table 4-3 (in £ and €). The table also shows 
the material revenues assumed as part of the original analysis and how they have 
been updated in the revised model.  

Table 4-3: Updated Material Revenues 

Average material 
prices (£ per tonne) 
based on UK Material 
Pricing Report (covers 
weekly average prices 
over period June 2013 
- June 2015) 

Average Material 
Prices (€ per 
tonne) based on 
two year 
average £/€ 
exchange rate 
(Jun 2013 - Jun 
2015) 

Old Material 
Revenues in the 
European 
Reference Model 
on Municipal 
Waste 
Management (€ 
per tonne, 2013 
prices)1 

Updated material 
revenues use in 
revised model (€ 
per tonne, 2015 
prices) 

£882 

£623 

-  

£3194 

£195 

£126 

£759 

- 

£916 

€110 

€78 

- 

€399 

€24 

€157 

€948 

- 

€113 

€ 118 

€ 106 

- 

€ 296 

€ 24 

- 

- 

€ 274 

€ 118 

€110 

€78 

€947 

€ 2968 

€24 

€157 

€948 

€3159 

€113 

Material 

Paper 

Card 

Mixed paper and card 

Textiles 

Glass 

Steel cans 

Aluminium cans 

Metals 

Plastics 

7 WRAP and MRW (2015) Material Pricing Report, June 2015, 
www.mrw.co.uk/Journals/2015/07/06/s/c/o/MPR-raw-data-15-June-2015.xls 
8 WRAP and MRW (2015) Material Pricing Report, June 2015, 
www.mrw.co.uk/Journals/2015/07/06/s/c/o/MPR-raw-data-15-June-2015.xls 

9 Eurostat (2015) Euro/national currency exchange rates [teimf200], Date Accessed: July 2014, Available at: 
http://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=teimf200&plugin=1  

28/05/2015 

25 

 
                                                   
 
Notes:  

1.  Revenue data cited in Appendix 5 of Eunomia Research & Consulting, and Copenhagen Resource 

Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

2.  Average of ‘New & Pams’ midpoint price. 
3.  Subtracted £10 per tonne from the Old Corrugate Container (OCC) domestic midpoint market price 

and took an average of this. The price was reduced to account for lower grade materials collected via 
comingled waste streams and to provide a conservative estimate of the likely revenues. 
4.  Average midpoint price for textiles collected by UK municipalities. This figure is unlikely to be 

representative of other Member States and thus the original figure of €296 per tonne has been 
maintained.  

5.  Average midpoint price for mixed glass. 
6.  Average midpoint price for mixed polymer plastic bottles. 
7.  The Municipal Waste Model takes a simplified approach and assumes a single revenue stream for 

paper and card. This figure is the average of the paper and card revenues.  

8.  The figures from the Material Pricing Report are unlikely to be representative of other Member States 

and thus the original figure of €296 per tonne has been maintained. 

9.  The Municipal Waste Model assumes that metals are made up of 80% ferrous cans and 20% non-

ferrous cans. This figure is therefore a weighted average of the steel and aluminium can revenues.  

4.5 

Losses from Sorting and Reprocessing Facilities 

It is clear that there are various stages at which losses can occur in the passage of materials 
from the point at which they are collected to the point at which they are actually recycled. 
Appendix 5 of the waste model documentation reviews some of the available literature on 
loss rates from different collection systems and reprocessors (readers are referred to this 
appendix for more details).10 The model could not hope to specify loss rates for each 
material in each of the many service configurations which exist. The pragmatic approach 
taken to the collection modelling has meant that the model specifies loss rates for a range 
of system types and materials. In the model, the loss rate assumptions shown in Table 4-4 
are applied to the quantities of dry recyclables collected for recycling in each Member State. 
With regards to biowaste it was assumed that all material collected for recycling was 
recycled (i.e. a 0% loss rate was assumed). It is important to note that these loss rates apply 
to materials which are rejected as residual waste at both the sorting and the reprocessing 
phases (i.e. they account for all material losses that may arise after materials have been 
collected for recycling).  

10 See for example: GVM (2011) Recycling-Bilanz fur Verpackungen: Berichtsjahr 2010, (Translation: Recycling 
Balance Sheet for Packaging: 2010 Report), December 2011; WRAP (2009) MRF Quality Assessment Study, 
www.wrap.org.uk/sites/files/wrap/MRF%20Quality%20Assessment%20Study.pdf; Luca Stramare (2013) 
Managing Post-Consumer Plastics Packaging Separate Collection: the COREPLA Experience, presentation at EPR 
Club / FEAD Seminar on EPR and Packaging, Brussels, 27 June 2013; Eunomia Research & Consulting (2011) The 
Impact of Rejects on the Recycling Rates of Local Authorities in Wales, Report for The Welsh Government, 
September 2011; Eunomia Research & Consulting, Resource Futures, and HCW Consultants (2011) Kerbside 
Collections Options: Wales, Report for WRAP, January 2011 

 
  
 
                                                   
 
Table 4-4: Loss Rate Assumptions on Collected Material Applied in the 
Reference Model 

Collection Operation 

Collection Route 

Material 

Associated Loss Rate (%) 

Bring Site 

Comingled Collection 

Door to Door 

CA Site 

Bring Site 

Materials Segregated 

Door to Door 

CA Site 

Paper & card 
Glass 
Metals 
Plastics 
Textiles 
Paper & card 
Glass 
Metals 
Plastics 
Textiles 
Paper & card 
Glass 
Metals 
Plastics 
Textiles 
Other  
Paper & card 
Glass 
Metals 
Plastics 
Textiles 
Paper & card 
Glass 
Metals 
Plastics 
Textiles 
Paper & card 
Glass 
Metals 
Plastics 
Textiles 
Other  

15% 
10% 
10% 
30% 
20% 
12% 
8% 
8% 
20% 
15% 
15% 
10% 
10% 
20% 
15% 
10% 
5% 
3% 
3% 
10% 
7% 
4% 
3% 
3% 
7% 
5% 
5% 
3% 
3% 
7% 
5% 
3% 

28/05/2015 

27 

 
 
 
 
 
5.0  Main Uncertainties Associated with the 

Model   

For the sake of clarity it is worth reiterating here what the Municipal Waste Model does and 
does not include. This section is taken directly from Section 4.0 of the main technical report 
which accompanies the model.11  

The modelling which forms the basis for the Impact Assessment is complex and incorporates 
a range of assumptions and variables which can be expected to influence the assessment. In 
the experience of the modelling team, and reflecting the nature of the model developed, 
the main uncertainties are set out below insofar as they affect the financial and the external 
costs. 

5.1 

Collection  

The model has, necessarily, to simplify somewhat the complexity of the situation which 
actually exists in Member States. In each country, there are, and are likely to be in future, a 
range of different collection systems in place. The model simplifies reality by modelling a 
narrow range of systems. However, although the range is narrowed, the general tendencies 
are expected to be a reasonable reflection of the relative costs of systems delivering varying 
recycling rates. 

The model makes assumptions which determine the number of households which can be 
served by a given vehicle. These are likely to vary from place to place. The model seeks to 
deal with this through setting different parameters for urban, suburban and rural 
households.  

The costs are modelled in real terms. They are essentially deemed to remain constant across 
time in real terms. The time horizon for the assessment is, however, considerable. Over such 
a period, the index of some input parameters to the collection model, such as labour costs, 
might not be the same as the general rate of price increases. As such, the costs might not 
remain constant in real terms over the time period considered. This is, however, believed to 
be the most reasonable assumption to make in the circumstances (projecting, for example, 
the rate of increase in real wages would appear to be rather speculative). 

The value of materials being captured for recycling is deemed to remain constant in real 
terms. Following a period in history (roughly spanning the period 1950-2000) over which 
real prices for commodities have experienced a secular decline, the last decade has seen 
that secular decline completely reversed owing to increased global demand, notably from 
China. Many commentators believe prices may continue to rise in real terms, but there are, 
equally reasons why prices, not least in real terms, may decline. As such, the assumption 

11 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
regarding constant prices in real terms seems not wholly unreasonable, albeit that any 
forecast of commodity prices in future is likely to be uncertain.  

For each country, where municipal waste is concerned, the model uses data from Member 
States regarding the composition of their municipal waste. The composition data is, in the 
model team’s view, of variable quality. Because of the variation in both waste quantity and 
waste composition from one country to another, the revenue generated from the capture of 
recyclables varies across countries (affecting net costs).  

Quite apart from current waste composition, the modelling effectively has to consider waste 
composition over the period to 2035. Relatively little is known about exactly how waste 
composition will change in future. What seems certain, however, is that it will change. It is 
to be hoped that those changes that do occur will increase the extent to which materials 
can be easily recycled. What cannot be known, however, is how such changes will affect the 
costs of collecting and processing materials, and the revenues generated from selling the 
materials collected. The assumption of constant composition is on the one hand unlikely to 
reflect reality, but on the other, it is felt that no reasonable alternative assumption exists. 

5.2 

Treatment  

The costs of treatment are assumed to remain constant in real terms. For some treatments, 
as well as taking into account the sale of some materials (see above for a discussion) the net 
costs take into account the sales of energy. The revenue derived from the sales of energy 
are assumed to be constant in real terms. This implies constant real terms prices for energy. 
Energy prices could, of course, follow a different path; 

The costs are influenced by assumptions regarding capital costs, assumed to be constant 
across countries, and the costs of other inputs to the process. Labour costs have been 
adapted to reflect Member State labour costs. There is variation in unit capital costs of 
facilities, but the model assumes a single figure for a given treatment. This seems 
reasonable given that the high level, strategic nature of the model means that assumptions 
regarding the size of specific facilities cannot meaningfully be made; 

The way in which capital costs are financed will affect the costs for different facilities. In 
different Member State, there are different patterns of financing and ownership of waste 
management facilities. Some facilities are funded from savings made by municipalities, 
whilst others are financed using public / private partnerships. These situations lead to a 
variety in the costs of capital, and this affects the costs of operating facilities. The model 
effectively assumes a single figure for the real costs of capital. The central figure is more 
representative of projects where the private sector is involved.  

5.3 

Externalities 

The overall figures for externalities reflect the inclusion and exclusion of various effects in 
the model. We believe that the main externalities of well operated facilities are captured by 
the model, but even so, some externalities are not captured by the model (see Section 4.0 
of the main technical report which accompanies the model). 

The model assumes different damage costs for the air pollutants with these adapted for 
each Member State. These are based on the best evidence available, but clearly, 
uncertainties exist. 

28/05/2015 

29 

 
The model assumes a profile for the damages associated with GHG emissions. The debate 
concerning how best to value damages associated with GHGs continues apace. There are 
clearly alternative assumptions that could be made in this regard. 

Some characteristics of key processes influence emissions, and hence, externalities. Key 
amongst these are: 

  The modelling of the extent to which biodegradable material degrades in landfill; 

  The capture of methane generated by landfills for energy generation and flaring (and 

crucially, the amount of methane escaping to the atmosphere); 

  For technologies generating energy, such as incineration, the nature of the energy 
source which is assumed to be avoided, at the margin, when new facilities are 
introduced; and 

  The modelled GHG emissions from facilities relate back to waste composition. If 

composition is not well known, then the emissions will be similarly poorly 
understood (and as noted above, composition is likely to change in future). 

5.4 

Prevention Impacts 

Impacts with respect to waste prevention initiatives, and costs of individual initiatives that 
might be run, are not well documented in the literature and likely, in practice, to vary from 
one situation to the next depending on the manner in which initiatives are enacted (for 
example, there are many permutations of pay as you throw schemes). Capabilities are 
included in the model to account for the waste prevention impacts and the costs associated 
with prevention initiatives, and some default values are included to aid the functioning of 
the model. It should be recognised that the default values are based on limited evidence. It 
is intended that Member States should enter bespoke values if national prevention 
initiatives are being considered. Prevention, and additional generation impacts are also 
described in Appendix 5 for the case where a change in the overall generation of waste 
results from the implementation of certain collection services; evidence is called on where 
available from the literature, and from experience following collection services changes in 
practice, but the modelled values are selected to be conservative.   

5.5 

Summary 

It will be clear from the above that the model is complex, and that the results are likely to 
vary with the nature of assumptions made.12 That having been said, considerable efforts 
have been made to ensure assumptions are reasonable, and the modelling is based on the 
best information available. The financial and environmental modelling has been subject to 
peer review. 

As described in the main report the Municipal Waste Model has an inbuilt sensitivity test 
tool in order to test how sensitive the output results are to changes in key assumptions (see 
Section 2.0). It is important to note that despite these uncertainties the key messages of the 

12 The modelling results presented in this report were generated in April 2015 after a period of further 
development and upgrade to the Municipal Waste Model. The changes to the model are noted in Section 3.0. 

 
                                                   
 
results do not change. Although the absolute numbers change as one flexes the 
assumptions between realistic upper and lower bounds the overall narrative and trends do 
not appear to change.  

28/05/2015 

31 

 
 
 
6.0  Member State Data Tables 

The Member State summary reports presented in Sections 7.0 to 34.0 are intended to help 
Member States understand the key parameters which underpin the analysis that was 
undertaken as part of the Impact Assessment and explain how the model results were 
derived. It is hoped that that the summary reports will provide greater transparency and 
clarity in the results, and demonstrate what type of outputs can be generated by the 
Municipal Waste Model. In addition to the summary reports 28 Excel based ‘Member State 
Data Tables’ have been created to accompany this Appendix, one for each Member State. 
These Data Tables provide detailed outputs from the model and are referred to in the 
summary reports below.   

Other than for input assumptions (e.g. waste composition) the summary reports and Data 
Temples present results relating to the 2030 70% preparation for reuse and recycling 
scenario for municipal waste.13 As in the impact assessment, all results are shown relative to 
a scenario in which the existing targets in the Waste Framework and Landfill Directives are 
being met (this scenario is known as ‘Full Implementation’).   

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.14 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.15 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For each country the Member State Data Table has a total of 62 tables which present a 
wider range of data. However, only a small number of these are referred to in the summary 

13 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
14 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
15 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
reports which follow. A full list of the data tables included in the Data Tables is presented in 
Box 2. 

Box 2: Member State Data Table Contents 

WASTE GENERATION 

Waste Arisings 

Table 1 - Projected Waste Arisings, 2011-2030, thousand tonnes 

Waste Composition 

Table 2 - Waste Composition 

Waste Prevented 

Table 3 - Waste Prevented through Initiatives under Full Implementation, thousand tonnes 
Table 4 - Waste Prevented through Initiatives under 70% Recycling, thousand tonnes 
Table 5 - Change in Waste Prevented through Initiatives - 70% Recycling vs Full Implementation 

Waste Prevention Effects 

Table 6 - Waste Prevention Effects of Collection Systems under Full Implementation, 2015-2030 
Table 7 - Waste Prevention Effects of Collection Systems under 70% Recycling, 2015-2030 
Table 8 - Change in Waste Prevention Effects of Collection Systems - 70% Recycling vs Full 
Implementation, 2015-2030 

WASTE COLLECTION 

Variation in Collection Systems 

Table 9 - Variation in Collection System Types under both Scenarios, 2030, thousand households 
Table 10 - Households on Key Services under Full Implementation, thousand households 
Table 11 - Households on Key Services under 70% Recycling, thousand households 

Waste Collected 

Table 12 - Waste Collected under Full Implementation, 2030 
Table 13 - Waste Collected under 70% Recycling, 2030 
Table 14 - Change in Waste Collected - 70% Recycling vs Full Implementation 

WASTE MANAGEMENT DESTINATIONS 

Recycling Rate 

Table 15 - Change in the Components of Overall Recycling Rate as a Proportion of Total Municipal 
Waste, 2030 
Table 16 - Recycling by Material under Full Implementation, thousand tonnes 
Table 17 - Recycling by Material under 70% Recycling, thousand tonnes 

Waste Management (Direct Inputs) 

Table 18 - Change in Waste Management Destinations (Direct Inputs) under Full Implementation, 
2015-2030, thousand tonnes 
Table 19 - Change in Waste Management Destinations (Direct Inputs) under 70% Recycling, 2015-
2030, thousand tonnes 
Table 20 - Change in Waste Management Destinations (Direct Inputs) - 70% Recycling vs Full 
Implementation, 2015-2030, thousand tonnes 

Waste Management (Final Destination) 

Table 21 - Change in Waste Management (Final Destinations) under Full Implementation, 2015-2030, 
% 
Table 22 - Change in Waste Management (Final Destinations) under 70% Recycling, 2015-2030, % 
Table 23 - Change in Waste Management Destinations (Final Destinations) - 70% Recycling vs Full 
Implementation, 2015-2030, % 

Residual Waste Treatment 

Table 24 - Direct Inputs to Residual Waste Treatment Plants as a Proportion of Total Municipal Waste 
Table 25 - Change in the Treatment of Residual Waste (Direct Inputs), 2030, thousand tonnes 
Table 26 - Change in the Treatment of Residual Waste (Final Inputs), 2030, thousand tonnes 

FINANCIAL COSTS - WASTE COLLECTION 

28/05/2015 

33 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Waste Collection Assumptions 

Table 27 - Waste Collection Assumptions 

Collection Costs for Recycling and Refuse 

Table 28 - Collection Costs for Recycling and Refuse (2015 Real Term Prices) 

Costs of Civic Amenity Sites 

Table 29 - Costs of Civic Amenity Sites (Container Parks) (2015 Real Term Prices) 

Summary Collection Costs 

Table 30 - Summary Collection Costs (2015 Real Term Prices) 
Table 31 - Change in Waste Collection Costs under Full Implementation, 2015-2030 (2015 Real Term 
Prices) 
Table 32 - Change in Waste Collection Costs under 70% Recycling, 2015-2030 (2015 Real Term Prices) 
Table 33 - Change in Waste Collection Costs - 70% Recycling vs Full Implementation, 2015-2030 
(2015 Real Term Prices) 

Material Revenue 

Table 34 - Material Revenue Achieved in 2030 (2015 Real Term Prices) 

FINANCIAL COSTS - WASTE TREATMENT 

Energy Revenue Assumptions 

Table 35 - Assumed Energy Revenues for Generators, € (2015 Prices)  

Waste Treatment 

Table 36 - Summary of Waste Treatment Costs in 2030 (2015 Real Term Prices) 

TOTAL FINANCIAL COSTS 

Table 37 - Total Financial Costs in 2030, million € (2015 Real Term Prices) 
Table 38 - Change in Financial Costs under Full Implementation, 2015-2030, million € (2015 Real 
Term Prices) 
Table 39 - Change in Financial Costs under 70% Recycling, 2015-2030, million € (2015 Real Term 
Prices) 
Table 40 - Change in Financial Costs - 70% Recycling vs Full Implementation, 2015-2030, million € 
(2015 Real Term Prices) 

ENVIRONMENTAL COSTS 

Key Environmental Assumptions 

Table 41 - Key Environmental Assumptions, 2030 

GHG Tonnage Impacts 

Table 42 - Summary of GHG Tonnage Impacts in 2030, thousand tonnes CO2 equivalent 
Table 43 - Change in GHG Tonnage Impacts under Full Implementation, 2015-2030, thousand tonnes 
CO2 equivalent 
Table 44 - Change in GHG Tonnage Impacts under 70% Recycling, 2015-2030, thousand tonnes CO2 
equivalent 
Table 45 - Change in GHG Tonnage Impacts - 70% Recycling vs Full Implementation, 2015-2030, 
thousand tonnes CO2 equivalent 

Average External Costs per Tonne 

Table 46 - Average External Costs per Tonne in 2030 (2015 Real Term Prices) 

Change in External Costs 

Table 47 - Change in External Costs in 2030 (2015 Real Term Prices) 
Table 48 - Change in External Costs under Full Implementation, 2015-2030, million € (2015 Real Term 
Prices) 
Table 49 - Change in External Costs under 70% Recycling, 2015-2030, million € (2015 Real Term 
Prices) 
Table 50 - Change in External Costs - 70% Recycling vs Full Implementation, 2015-2030, million € 
(2015 Real Term Prices) 

EMPLOYMENT 

Table 51 - Summary of Employment Impacts in 2030, Number of FTE Employees 
Table 52 - Number of FTE Employees, Full Implementation, 2015-2030 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 53 - Number of FTE Employees, 70% Recycling, 2015-2030 
Table 54 - Number of FTE Employees - 70% Recycling vs Full Implementation, 2015-2030 

NET SOCIAL COSTS 

Net Social Costs Summary 

Table 55 - Costs and Benefits Summary (2015 Real Term Prices) 
Table 56 - Net Social Costs under Full Implementation, 2015-2030, million € (2015 Real Term Prices) 
Table 57 - Net Social Costs under 70% Recycling, 2015-2030, million € (2015 Real Term Prices) 
Table 58 - Net Social Costs - 70% Recycling vs Full Implementation, 2015-2030, million € (2015 Real 
Term Prices) 

RESOURCE EFFICIENCY INDICATORS 

Resource Efficiency Indicators 

Table 59 - Resource Efficiency Summary, 2030 
Table 60 - Resource Efficiency Indicators under Full Implementation, 2015-2030 
Table 61 - Resource Efficiency Indicators under 70% Recycling, 2015-2030 
Table 62 - Resource Efficiency Indicators - 70% Recycling vs Full Implementation, 2015-2030 

28/05/2015 

35 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7.0  Austria 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.16 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 7-1 
shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.17 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.18 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.3 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

16 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
17 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
18 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with just under half of the benefit coming from reduced environmental 
externalities and just over half from reduced financial costs.  

Table 7-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)19 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.13 

-€ 0.17 

-€ 0.30 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

7.1  Waste Generation and Management Projections 

The data used is based on the Austrian Federal Ministry of Agriculture, Forestry, 
Environment and Water Management, and also some information from the Environment 
Agency in Austria. In addition, further information was gathered via a detailed questionnaire 
which was specifically developed to gather the required input data for the model. For 
collection, this is primarily based on internal data compiled by Eunomia. 

19 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

28/05/2015 

37 

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

7.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 7-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.20  

MSW generation projections assume an increase in waste generated of 1% per year. The 
details of these projections are discussed in the technical documentation which 
accompanies the Municipal Waste Model.21 Interested readers should refer to this 
documentation for further details.  

Table 7-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

4,756 

4,917 

5,167 

5,431 

5,708 

Full Implementation Scenario (a) 

4,756 

4,917 

5,167 

5,431 

5,708 

70% Recycling Target Scenario (b) 

4,756 

4,917 

5,167 

5,419 

5,681 

Difference (b – a) 

0 

0 

0 

-12 

-27 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 

20 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
21 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Austria the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.22 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Austria’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

7.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 7-3. It is interesting to note 
that Austria has chosen to calculate the Waste Framework Directive recycling target of 50% 
by means of calculation method 2, which the model estimates at 66%. However, the model 
suggests that the total MSW recycling rate in 2020 (e.g. method 4) would be higher than the 
target (55%), suggesting Austria would meet the target even if method 4 had been selected.  

22 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

39 

 
                                                   
 
Table 7-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

60% 

5.0% 

0.5% 

56% 

4.5% 

93% 

76% 

6.9% 

0.2% 

69% 

6.7% 

91% 

16% 

2.0% 

-0.3% 

13% 

2.2% 

-1.4% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 4.5% 
and 6.7% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.23 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Austria is 13% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

7.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 7-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 

23 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
                                                   
 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Austria the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 60%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 76% (Table 7-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 7-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion of 
Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

14% 

26% 

40% 

60% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 7-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

776 

1,496 

0 

2,271 

42% 

468 

903 

0 

1,372 

29% 

-307 

-592 

0 

-900 

-13% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

28/05/2015 

41 

 
  
 
7.2  Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.24  Table 7-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 7-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

3 

654 

571 

0 

0 

0 

0 

0 

-3 

27 

-627 

1,201 

630 

Source: European Reference Model on Municipal Waste Management. 

7.3 

Financial Costs 

7.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 7-7 shows some of the key waste collection assumptions 
used in the modelling.  

24 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
 
                                                   
 
Table 7-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

101.3 

64 

36 

Labour Costs 

Mean Net Annual Earnings 

30,819 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

21 

26 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

58,369 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

28/05/2015 

43 

 
 
Table 7-8: Summary of Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 195 

€ 114 

€ 49 

€ 0 

€ 359 

€ 198 

€ 97 

€ 61 

€ 6 

€ 363 

€ 3 

-€ 17 

€ 12 

€ 6 

€ 5 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

7.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.25 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Austria are shown in Table 7-9. 

25 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                   
 
Table 7-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 56.21 

€ 65.45 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

7.3.3  Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 7-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 7-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 363 

€ 249 

€ 612 

€ 359 

€ 317 

€ 676 

€ 5 

-€ 68 

-€ 64 

Source: European Reference Model on Municipal Waste Management. 

7.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.26 A number of the key country 
specific assumptions which have been made are shown in Table 7-11 

26 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

45 

 
                                                   
 
Table 7-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Marginal Heat Mix 

18 

7 

0 

3 

72 

147 

43 

5 

10 

33 

9 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

140 

Kg CO2 eq / MWh 

25 

14 

42 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data 
Table.The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As 
noted above, further detail and explanations about these externalities can be found in 

 
Appendix 6 of the technical documentation which accompanies the Municipal Waste 
Model.27 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 7-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 7-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

€ 0 

-€ 5,474 

-€ 5,474 

-€ 53,602 

-€ 76,851 

-€ 23,248 

€ 8,071 

€ 8,040 

€ 4,915 

€ 4,895 

€ 3,050 

€ 3,043 

€ 370 

€ 369 

€ 1,571 

€ 1,567 

-€ 31 

-€ 20 

-€ 8 

-€ 1 

-€ 4 

-€ 1 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

AD - Gas to Vehicle Fuel 

€ 275 

€ 275 

Electricity Only 

€ 55,880 

€ 41,532 

-€ 14,348 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 1,806 

€ 1,176 

-€ 630 

Biodrying with no Plastics Recycling 

€ 0 

€ 0 

€ 0 

Biodrying with Plastics Recycling 

€ 7,759 

€ 4,809 

-€ 2,951 

AD based MBT 

€ 2,561 

€ 1,600 

Residual MRF + Combustion 

€ 2,076 

€ 1,262 

Landfill 

€ 0 

-€ 962 

-€ 814 

€ 0 

27 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

47 

 
 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 3 

€ 5 

€ 2 

Total 

€ 34,737 

-€ 13,753 

-€ 48,490 

Source: European Reference Model on Municipal Waste Management. 

7.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 7-1 and Table 7-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 3.1 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

 
Figure 7-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 7-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 35 

-€ 14 

-€ 48 

€ 0.4 

€ 0.2 

-€ 0.13 

Financial Costs (social metric) 

€ 676 

€ 612 

-€ 64 

Net Costs and Benefits 

€ 711 

€ 598 

-€ 112 

Source: European Reference Model on Municipal Waste Management. 

€ 7.4 

€ 7.8 

€ 7.3 

-€ 0.17 

€ 7.5 

-€ 0.30 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Austria depends on 

28/05/2015 

49 

-€120-€100-€80-€60-€40-€20€020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 1.8 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects.  

 
 
 
8.0  Belgium 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.28 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
8-1shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.29 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.30 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.3 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

28 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
29 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
30 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

51 

 
                                                   
 
value terms, with just over half of the benefit coming from reduced environmental 
externalities and just under half from reduced financial costs.  

Table 8-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)31 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.15 

-€ 0.08 

-€ 0.23 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

8.1  Waste Generation and Management Projections 

Information was provided by the Public Waste Agency of Flanders, Openbare Vlaams 
Afvalstoffenmaatschappij (OVAM), the Direction de l'Etat Environnemental, Wallonia, and 
the IBGE - Bruxelles Environnement/BIM - Leefmilieu Brussels, via return of a detailed 

31 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

 
 
                                                   
 
questionnaire which was specifically developed to gather the required input data for the 
model.32 

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

8.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 8-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.33  

The methodology used to estimate MSW generation projections for Belgium is available 
from Andersen et al. (2007).34 The details of these projections are discussed in the technical 
documentation which accompanies the Municipal Waste Model. 35 Interested readers should 
refer to this documentation for further details.  

Table 8-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

5,125 

5,297 

5,497 

5,669 

5,818 

Full Implementation Scenario (a) 

5,125 

5,297 

5,497 

5,669 

5,818 

70% Recycling Target Scenario (b) 

5,125 

5,297 

5,497 

5,641 

5,759 

Difference (b – a) 

0 

0 

0 

-28 

-60 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

32 OVAM, (2013) Questionnaire information returned, Direction de l'Etat Environnemental, (2013) 
Questionnaire information returned, IBGE/BIM, (2013) Questionnaire information returned. 
33 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
34 Andersen, F. M., Larsen, H., Skovgaard, M., Moll, S. and Isoard, S. (2007) A European Model for Waste and 
Material ﬂows, Resources, Conservation and Recycling, Vol.49, pp. 421–435 
35 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

53 

 
                                                   
 
The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Belgium, the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.36 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Belgiums’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

8.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 8-3. Belgium has chosen to 
calculate the Waste Framework Directive recycling target of 50% by means of calculation 

36 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
method 4, which the model estimates at 54%. Therefore, the target is expected to be met 
even if calculated based upon the total amount of MSW recycled. 

Table 8-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

58% 

4.6% 

0.1% 

54% 

4.5% 

92% 

76% 

6.3% 

0.0% 

70% 

6.3% 

92% 

18% 

1.7% 

0.0% 

16% 

1.7% 

-0.4% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 4.5% 
and 6.3% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.37 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Belgium is 16% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

8.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 8-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 

37 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

55 

 
 
                                                   
 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Belgium the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 59%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 76% (Table 7-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 8-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion of 
Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

1% 

40% 

41% 

59% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 8-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

58 

32 

-26 

Direct Inputs to Incineration Plants 

2,322 

1,299 

-1,023 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

58 

2,438 

44% 

32 

1,364 

28% 

-26 

-1,074 

-16% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

 
  
 
8.2  Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.38  Table 8-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 8-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

6 

237 

113 

0 

0 

0 

17 

339 

0 

0 

-6 

-220 

226 

Source: European Reference Model on Municipal Waste Management. 

8.3 

Financial Costs 

8.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 7-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 8-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

38 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

57 

 
 
 
                                                   
 
Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

108.4 

95 

5 

Labour Costs 

Mean Net Annual Earnings 

32,732 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

26 

31 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

77,073 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  
1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 8-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

 
 
 
 
 
Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

Million € 

€ 299 

€ 142 

€ 82 

€ 12 

€ 536 

€ 261 

€ 170 

€ 67 

€ 3 

€ 501 

€ 38 

-€ 27 

€ 15 

€ 9 

€ 35 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

8.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.39 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. 

It is important to note that these costs do not represent the gate fees charged at these 
facilities, but have been calculated to represent actual resource costs, excluding taxes and 
transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Belgium are shown in Table 8-9. 

39 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

59 

 
 
                                                   
 
Table 8-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 
Revenue from Heat Sales 

€ 60.29 
€ 50.13 

€ per MWh 
€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

8.3.3  Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 8-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 8-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 536 

€ 224 

€ 760 

€ 501 

€ 298 

€ 799 

€ 35 

-€ 74 

-€ 39 

Source: European Reference Model on Municipal Waste Management. 

8.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.40 A number of the key country 
specific assumptions which have been made are shown in Table 8-11. 

Table 8-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

32 

% 

40 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Assumption 

Value 

Unit 

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

7 

52 

7 

2 

% 

% 

% 

% 

227 

Kg CO2 eq / MWh 

Marginal Heat Mix 

86 

0 

0 

2 

12 

190 

25 

14 

42 

80 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.41 

41 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

61 

 
                                                   
 
The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 8-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 8-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 0 

-€ 13,539 

-€ 13,539 

-€ 54,300 

-€ 72,346 

-€ 18,046 

€ 9,977 

€ 12,996 

€ 3,019 

€ 4,619 

€ 5,620 

€ 1,001 

€ 1,170 

€ 1,400 

€ 230 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Electricity Only 

€ 51,685 

€ 31,330 

-€ 20,355 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Residual MRF + Combustion 

€ 908 

€ 448 

-€ 460 

Landfill 

€ 3,104 

€ 1,880 

-€ 1,224 

Collection and Sorting 

€ 4 

€ 5 

€ 1 

Total 

€ 17,167 

-€ 32,206 

-€ 49,373 

Source: European Reference Model on Municipal Waste Management. 

8.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 8-1 and Table 8-13. From this it is clear 

 
 
 
 
 
 
 
 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 1.2 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

28/05/2015 

63 

 
Figure 8-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 8-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 17 

-€ 32 

-€ 49 

€ 0.2 

€ 0.1 

-€ 0.15 

Financial Costs (social metric) 

€ 799 

€ 760 

-€ 39 

Net Costs and Benefits 

€ 816 

€ 728 

-€ 88 

Source: European Reference Model on Municipal Waste Management. 

€ 8.9 

€ 9.1 

€ 8.8 

-€ 0.08 

€ 8.9 

-€ 0.23 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Belgium depends 

-€90-€80-€70-€60-€50-€40-€30-€20-€10€0€1020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
 
on the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 1.3 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

28/05/2015 

65 

 
 
 
9.0  Bulgaria 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.42 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 9-1 
shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.43 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.44 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.14 billion (in 2014 real term prices) over the period from 2014-2030 in net 

42 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
43 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
44 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
present value terms, with around two thirds of the benefit coming from reduced 
environmental externalities and one third from reduced financial costs.  

Table 9-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)45 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.07 

-€ 0.01 

-€ 0.08 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

9.1  Waste Generation and Management Projections 

As with all other Member States information was gathered via a detailed questionnaire 
which was specifically developed to gather the required input data for the model. A contact 
at the Bulgarian Ministry of Environment’s Department of Municipal and Construction 
Waste Management completed the questionnaire ahead of a face-to-face meeting in 
Bulgaria. This contact also provided some additional feedback on a number of subsequent 
queries that were raised while developing this baseline report. 

45 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

28/05/2015 

67 

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

9.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 9-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.46  

Future municipal waste arisings have not yet been modelled and released by the Bulgarian 
government. While waste generation projections have previously been developed by the 
Copenhagen Resource Institute in 2012, these rely on Eurostat data, and it became clear, 
after an in-country meeting with the Bulgarian Ministry of the Environment, that the data 
reported to Eurostat in the past has not been a reliable basis on which to develop 
projections. Therefore, in the absence of better data, a zero growth rate is assumed for 
municipal waste. Further details of these projections are discussed in the technical 
documentation which accompanies the Municipal Waste Model. 47 Interested readers should 
refer to this documentation for further details.  

Table 9-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

3,000 

3,000 

3,000 

3,000 

3,000 

Full Implementation Scenario (a) 

3,000 

3,000 

3,080 

3,077 

3,074 

70% Recycling Target Scenario (b) 

3,000 

3,000 

3,080 

3,060 

3,054 

Difference (b – a) 

0 

0 

0 

-17 

-20 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

46 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
47 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Bulgaria, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.48 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.49 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Bulgaria’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

9.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

48 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
49 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

69 

 
                                                   
 
2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 9-3. It is important to note 
that Bulgaria has chosen to meet the 50% recycling target by means of calculation method 
3. Given the nature of this calculation method the country will have to achieve the target by 
recycling 50% of the total municipal waste stream (see Full Implementation scenario in the 
table below which assumes full compliance with the Waste Framework Directive target by 
the county’s chosen calculation method). The 50% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.50 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.51 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 9-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

54% 

4.4% 

0.1% 

50% 

4.3% 

92% 

70% 

5.9% 

0.1% 

65% 

5.8% 

92% 

16% 

1.5% 

0.0% 

15% 

1.5% 

-0.3% 

50 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
51 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
Full 
Implementation 

70% Recycling 
Target 

Difference 

Note:  

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Bulgaria has chosen Method 3 to calculate the country’s performance against the WFD target of 50%. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 4.3% 
and 7.2% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.52 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Bulgaria is 20% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

9.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 9-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Bulgaria the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 91%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 77% (Table 9-3), waste will not have to be diverted 
from the planned MBT and incineration plants. 

Table 9-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion of 
Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

10% 

Full Implementation 

52 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

71 

 
 
  
                                                   
 
Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

0% 

10% 

90% 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 9-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

297 

0 

1,109 

1,406 

50% 

191 

0 

713 

904 

35% 

-106 

0 

-395 

-501 

-15% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

9.2  Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.53  Table 9-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 

53 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
  
 
                                                   
 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 9-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

27 

731 

337 

0 

0 

0 

132 

963 

0 

0 

-27 

-598 

626 

Source: European Reference Model on Municipal Waste Management. 

9.3 

Financial Costs 

9.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 9-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 9-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

Labour Costs 

Mean Net Annual Earnings 

Tax rate (% of salary) 

128.9 

48 

52 

4,263 

21 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

28/05/2015 

73 

 
 
Assumption 

Value 

Unit 

Source 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

14 

% 

Eurostat 

Mean Gross Annual Earnings 

6,577 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

2.5 

1.4 

2.5 

3.8 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Collection Frequencies 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 9-8: Summary of Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 106 

€ 84 

€ 21 

€ 11 

€ 222 

€ 115 

€ 67 

€ 31 

€ 17 

€ 230 

€ 9 

-€ 17 

€ 10 

€ 6 

€ 8 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

 
 
 
 
9.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.54 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. 

It is important to note that these costs do not represent the gate fees charged at these 
facilities, but have been calculated to represent actual resource costs, excluding taxes and 
transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Bulgaria are shown in Table 9-9. 

Table 9-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 46.13 

€ 25.43 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

9.3.3  Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 9-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

54 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

75 

 
                                                   
 
Table 9-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 230 

€ 82 

€ 312 

€ 222 

€ 93 

€ 315 

Source: European Reference Model on Municipal Waste Management. 

9.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.55 A number of the key country 
specific assumptions which have been made are shown in Table 7-11 

Table 9-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

5 

49 

31 

1 

14 

418 

Kg CO2 eq / MWh 

Marginal Heat Mix 

48 

37 

9 

0 

% 

% 

% 

% 

€ 8 

-€ 11 

-€ 3 

% 

% 

% 

% 

% 

55 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

6 

239 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.56 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 9-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 9-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

-€ 4,201 

-€ 7,167 

-€ 2,966 

-€ 29,097 

-€ 33,436 

-€ 4,339 

€ 1,919 

€ 2,362 

€ 1,672 

€ 2,047 

€ 697 

€ 45 

€ 897 

€ 58 

€ 444 

€ 374 

€ 200 

€ 13 

56 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

77 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

€ 844 

€ 190 

€ 1,083 

€ 245 

€ 239 

€ 55 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

AD based MBT 

€ 2,091 

€ 1,357 

-€ 734 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

Landfill 

€ 51,845 

€ 37,361 

-€ 14,484 

Collection and Sorting 

€ 2 

€ 2 

€ 0 

Total 

€ 26,007 

€ 4,808 

-€ 21,199 

Source: European Reference Model on Municipal Waste Management. 

9.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 7-1 and Table 7-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 1.9 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 9-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 9-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

28/05/2015 

79 

-€25-€20-€15-€10-€5€020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 26 

€ 5 

-€ 21 

€ 0.3 

€ 0.2 

-€ 0.07 

Financial Costs (social metric) 

€ 315 

€ 312 

-€ 3 

Net Costs and Benefits 

€ 341 

€ 317 

-€ 24 

Source: European Reference Model on Municipal Waste Management. 

€ 3.6 

€ 3.8 

€ 3.5 

-€ 0.01 

€ 3.8 

-€ 0.08 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Bulgaria depends 
on the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 0.4 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects.

 
 
10.0  Croatia 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.57 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
10-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.58 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.59 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.38 billion (in 2014 real term prices) over the period from 2014-2030 in net 

57 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
58 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
59 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

81 

 
                                                   
 
present value terms, with around 40% of the benefit coming from reduced environmental 
externalities and 60% from reduced financial costs.  

Table 10-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)60 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.14 

-€ 0.07 

-€ 0.22 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

10.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Croatia with meetings 
held with the Ministry of Environment and Nature protection, the Croatian Environmental 
Agency (CEA) and the City of Zagreb Holding.61 In addition, further information was gathered 

60 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
61 CRI (2013, May 13th) Notes from meeting in Croatia with Ministry of Environment and Nature protection, 
the Croatian Environmental Agency (CEA) and the City of Zagreb Holding, including additional feedback 
received after the visit.   

 
 
                                                   
 
via a detailed questionnaire which was specifically developed to gather the required input 
data for the model. 

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

10.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 10-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.62  

MSW generation projections assume that municipal waste arisings grow at 1.5% per year. 
This assumption was used as projections developed by members of the project team, using 
the method described in Andersen et al. (2007) and Bakas et al. (2011), were thought to 
overestimate future waste arisings in Croatia.63,64 The details of these projections are 
discussed in the technical documentation which accompanies the Municipal Waste Model. 65 
Interested readers should refer to this documentation for further details. 

Table 10-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

1,630 

1,730 

1,864 

2,008 

2,163 

Full Implementation Scenario (a) 

1,630 

1,730 

2,009 

2,150 

2,303 

70% Recycling Target Scenario (b) 

1,630 

1,730 

2,009 

2,132 

2,278 

Difference (b – a) 

0 

0 

0 

-18 

-25 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

62 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
63 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
64 Bakas, I., Sieck, M., Hermann, T., Andersen, F. M. and Larsen, H. (2011). Projections of Municipal Waste 
Management and Greenhouse Gases. Prepared by Bakas et al., 89 pp. Copenhagen, Denmark 
65 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

83 

 
                                                   
 
The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Croatia, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.66 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.67 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Croatia’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

10.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

66 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
67 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 10-3. It is important to note 
that Croatia has chosen to meet the 50% recycling target by means of calculation method 2. 
Given the nature of this calculation method the country will be able to achieve the target by 
recycling 36% of the total municipal waste stream (see Full Implementation scenario in the 
table below which assumes full compliance with the Waste Framework Directive target by 
the county’s chosen calculation method). The 36% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.68 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.69 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 10-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

37% 

3.3% 

1.4% 

36% 

1.9% 

95% 

76% 

6.8% 

0.6% 

69% 

6.2% 

92% 

38% 

3.5% 

-0.9% 

34% 

4.4% 

-3.3% 

68 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
69 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

85 

 
 
                                                   
 
Full 
Implementation 

70% Recycling 
Target 

Difference 

Notes:  

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Croatia has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, which 
is met, but can be achieved by only recycling 36% of all municipal waste. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 1.9% 
and 6.1% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.70 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Croatia is 32% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

10.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 10-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Croatia the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 59%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 76% (Table 10-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 10-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

44% 

Full Implementation 

70 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
  
                                                   
 
Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

0% 

44% 

56% 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 10-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 10-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

1,016 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

0 

425 

1,441 

64% 

393 

0 

164 

557 

31% 

-623 

0 

-261 

-884 

-34% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

10.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.71  Table 10-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 

71 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

87 

 
  
 
 
                                                   
 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 10-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

170 

92 

0 

0 

0 

0 

4 

0 

0 

-170 

-88 

259 

259 

Source: European Reference Model on Municipal Waste Management. 

10.3 

Financial Costs 

10.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 10-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 10-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

138.0 

52 

48 

Labour Costs 

Mean Net Annual Earnings 

10,457 

Tax rate (% of salary) 

18 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

 
 
 
Assumption 

Value 

Unit 

Source 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

15 

% 

Eurostat 

Mean Gross Annual Earnings 

15,719 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

1.7 

1.4 

2.5 

3.8 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Collection Frequencies 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 10-8: Summary of Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 66 

€ 101 

€ 3 

€ 5 

€ 174 

€ 102 

€ 52 

€ 11 

€ 11 

€ 176 

€ 36 

-€ 48 

€ 8 

€ 6 

€ 2 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

28/05/2015 

89 

 
 
 
 
10.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.72 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. 

It is important to note that these costs do not represent the gate fees charged at these 
facilities, but have been calculated to represent actual resource costs, excluding taxes and 
transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Croatia are shown in Table 10-9. 

Table 10-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 57.56 

€ 38.50 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

10.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 10-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

72 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Table 10-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 176 

€ 67 

€ 243 

€ 174 

€ 93 

€ 267 

Source: European Reference Model on Municipal Waste Management. 

10.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.73 A number of the key country 
specific assumptions which have been made are shown in Table 10-11. 

Table 10-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

50 

30 

14 

1 

5 

446 

Kg CO2 eq / MWh 

Marginal Heat Mix 

100 

0 

0 

0 

% 

% 

% 

% 

€ 2 

-€ 26 

-€ 24 

% 

% 

% 

% 

% 

73 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

91 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

0 

200 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 

The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.74 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 10-12. Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 10-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

-€ 4,796 

-€ 9,960 

-€ 5,164 

Recycling 

-€ 26,457 

-€ 44,769 

-€ 18,312 

/

g
n
i
t
s
o
p
m
o
C

  Open Air Composting 
n
o
i
t
s
e
g
i
D

In-Vessel Composting 

AD - Electricity Only 

€ 1,048 

€ 2,924 

€ 1,876 

€ 717 

€ 110 

€ 1,834 

€ 1,117 

€ 498 

€ 388 

74 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

€ 12 

€ 236 

€ 31 

€ 0 

€ 0 

€ 0 

€ 0 

€ 53 

€ 1,029 

€ 148 

€ 0 

€ 0 

€ 0 

€ 0 

€ 41 

€ 794 

€ 117 

€ 0 

€ 0 

€ 0 

€ 0 

€ 17,068 

€ 5,269 

-€ 11,799 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Landfill 

€ 19,914 

€ 11,356 

-€ 8,558 

Collection and Sorting 

€ 1 

€ 2 

€ 1 

Total 

€ 7,885 

-€ 31,615 

-€ 39,500 

Source: European Reference Model on Municipal Waste Management. 

10.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 10-1 and Table 10-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 

28/05/2015 

93 

 
 
 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 3.3 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 10-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

-€70-€60-€50-€40-€30-€20-€10€0€1020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 10-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 8 

-€ 32 

-€ 40 

Financial Costs (social metric) 

€ 267 

€ 243 

-€ 24 

€ 0.2 

€ 2.6 

€ 0.0 

-€ 0.14 

€ 2.6 

-€ 0.07 

Net Costs and Benefits 

€ 275 

€ 211 

-€ 64 

€ 2.8 

€ 2.6 

-€ 0.22 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Croatia depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 2.9 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

28/05/2015 

95 

 
 
 
 
11.0  Cyprus 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.75 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
11-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.76 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.77 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.09 billion (in 2014 real term prices) over the period from 2014-2030 in net 

75 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
76 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
77 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
present value terms, with around one third of the benefit coming from reduced 
environmental externalities and two thirds from reduced financial costs.  

Table 11-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)78 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.04 

-€ 0.07 

-€ 0.12 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

11.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Cyprus with meetings 
held with representatives from the Ministry of Interior and the Ministry Of Environment. 79 
In addition, further information was gathered via a detailed questionnaire which was 
specifically developed to gather the required input data for the model.  

78 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
79 CRI (2013, June 26th) Notes from meeting in Cyprus with Cyprus national authorities, including additional 
feedback received after the visit.   

28/05/2015 

97 

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

11.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 7-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.80  

The MSW generation projections are based on a waste generation projection study made by 
the Cyprus Ministry of Environment. The details of these projections are discussed in the 
technical documentation which accompanies the Municipal Waste Model.81 Interested 
readers should refer to this documentation for further details. 

Table 11-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

Full Implementation Scenario (a) 

70% Recycling Target Scenario (b) 

Difference (b – a) 

574 

574 

574 

0 

584 

584 

584 

0 

602 

634 

634 

0 

611 

645 

641 

-4 

618 

653 

647 

-6 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 

80 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
81 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Cyprus, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.82 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.83 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Cyprus’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.    

11.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 11-3. It is important to note 
that Cyprus has chosen to meet the 50% recycling target by means of calculation method 1. 
Given the nature of this calculation method the country will be able to achieve the target by 

82 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
83 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

99 

 
                                                   
 
recycling 34% of the total municipal waste stream (see Full Implementation scenario in the 
table below which assumes full compliance with the Waste Framework Directive target by 
the county’s chosen calculation method). The 34% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.84 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.85 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 11-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

37% 

4.0% 

1.1% 

34% 

2.9% 

92% 

78% 

8.2% 

0.4% 

70% 

7.7% 

90% 

41% 

4.2% 

-0.7% 

36% 

4.9% 

-2.2% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Cyprus has chosen Method 1 to calculate the country’s performance against the WFD target of 50%, which is 
met, but can be achieved by only recycling 34% of all municipal waste. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 3.2% 
and 8.2% respectively more waste needs to be collected than the overall recycling rate to 

84 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
85 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.86 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Cyprus is 34% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

11.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 7-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Cyprus the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 56%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 7-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 11-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

47% 

0% 

47% 

53% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 

86 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

101 

 
  
                                                   
 
same (see Table 11-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 11-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

304 

0 

106 

411 

66% 

107 

0 

37 

144 

30% 

-197 

0 

-69 

-266 

-36% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

11.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.87  Table 11-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 11-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

0 

0 

0 

0 

0 

0 

87 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
 
                                                   
 
Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

22 

7 

0 

0 

0 

29 

-22 

-7 

29 

Source: European Reference Model on Municipal Waste Management. 

11.3 

Financial Costs 

11.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 11-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 11-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

123.9 

70 

30 

Labour Costs 

Mean Net Annual Earnings 

24,751 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

19 

17 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

28,809 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

1.7 

1.4 

Days between 
collections 

Eunomia 

Eunomia 

28/05/2015 

103 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

2.5 

3.8 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 11-8: Summary of Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 24 

€ 30 

€ 1 

€ 1 

€ 55 

€ 27 

€ 13 

€ 3 

€ 2 

€ 44 

€ 3 

-€ 17 

€ 2 

€ 1 

-€ 11 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table.

11.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.88 By way of summary, the calculated costs for different waste 

88 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 

 
 
 
 
 
                                                   
 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. 

It is important to note that these costs do not represent the gate fees charged at these 
facilities, but have been calculated to represent actual resource costs, excluding taxes and 
transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Cyprus are shown in Table 11-9. 

Table 11-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 134.72 

€ 0.00 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

11.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 11-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 11-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Cost Element 

Full Implementation 

70% Recycling Target 

Difference 

million € 

Collection Costs 

€ 55 

€ 44 

-€ 11 

Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

105 

 
                                                                                                                                                              
 
Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Treatment Costs 

Total Financial Costs 

million € 

€ 17 

€ 61 

€ 25 

€ 80 

Source: European Reference Model on Municipal Waste Management. 

11.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.89 A number of the key country 
specific assumptions which have been made are shown in Table 11-11. 

Table 11-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Marginal Heat Mix 

0 

0 

0 

100 

0 

600 

0 

5 

89 

6 

0 

-€ 8 

-€ 19 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

% 

89 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Assumption 

Value 

Unit 

Net carbon intensity 

238 

Kg CO2 eq / MWh 

Incinerator Generation Efficiencies 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

25 

14 

42 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 

The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.90 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 11-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 11-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

-€ 890 

-€ 1,764 

-€ 874 

-€ 7,051 

-€ 12,405 

-€ 5,354 

€ 632 

€ 238 

€ 0 

€ 0 

€ 1,027 

€ 1,233 

€ 0 

€ 0 

€ 394 

€ 995 

€ 0 

€ 0 

90 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

107 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 5,375 

€ 1,709 

-€ 3,666 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Landfill 

€ 6,719 

€ 4,442 

-€ 2,277 

Collection and Sorting 

€ 0 

€ 0 

€ 0 

Total 

€ 5,024 

-€ 5,757 

-€ 10,781 

Source: European Reference Model on Municipal Waste Management. 

11.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 11-1  and Table 11-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 1.3 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 11-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

28/05/2015 

109 

-€35-€30-€25-€20-€15-€10-€5€020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 11-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

€ 5 

€ 80 

€ 85 

-€ 6 

€ 61 

€ 55 

-€ 11 

-€ 19 

€ 0.1 

€ 0.8 

€ 0.0 

-€ 0.04 

€ 0.7 

-€ 0.07 

-€ 30 

€ 0.8 

€ 0.7 

-€ 0.12 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Cyprus depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 0.3 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects.

 
 
12.0  Czech Republic 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.91 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
12-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.92 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.93 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.7 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

91 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
92 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
93 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

111 

 
                                                   
 
value terms, with around one third of the benefit coming from reduced environmental 
externalities and two thirds from reduced financial costs.  

Table 12-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)94 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.24 

-€ 0.07 

-€ 0.31 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

12.1  Waste Generation and Management Projections 

As with all other Member States information was gathered via a detailed questionnaire 
which was specifically developed to gather the required input data for the model. A contact 
at the Czech Republic Ministry of Environment completed the questionnaire ahead of a 
face-to-face meeting. However, very little information was forthcoming and we were unable 
to clarify a number of follow up questions. As a result, much of the baseline information 

94 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

 
 
                                                   
 
required could not be verified. Where necessary, we have supplemented the information 
received with data from other sources. 

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

12.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 12-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.95  

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. 2007) and Bakas et al. (2011).96,97 The details of 
these projections are discussed in the technical documentation which accompanies the 
Municipal Waste Model.98 Interested readers should refer to this documentation for further 
details. 

Table 12-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

5,388 

5,563 

5,772 

5,989 

6,214 

Full Implementation Scenario (a) 

5,388 

5,563 

5,772 

5,989 

6,214 

70% Recycling Target Scenario (b) 

5,388 

5,563 

5,772 

5,961 

6,176 

Difference (b – a) 

0 

0 

0 

-28 

-38 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

95 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
96 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
97 Bakas, I., Sieck, M., Hermann, T., Andersen, F. M. and Larsen, H. (2011). Projections of Municipal Waste 
Management and Greenhouse Gases. Prepared by Bakas et al., 89 pp. Copenhagen, Denmark 
98 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

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The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of the Czech Republic, the waste prevention impacts of PAYT and food waste 
collections result in a net reduction in waste arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.99 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for the Czech Republic’s MSW stream is presented in Table 2 of 
the accompanying Member State Data Table.   

12.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 7-3. It is important to note 
that the Czech Republic has chosen to meet the 50% recycling target by means of 
calculation method 2. Given the nature of this calculation method the country will be able 

99 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
to achieve the target by recycling 32% of the total municipal waste stream (see Full 
Implementation scenario in the table below which assumes full compliance with the Waste 
Framework Directive target by the county’s chosen calculation method). The 32% overall 
recycling rate is based on the waste composition data and the projected municipal waste 
arisings that are saved in the Municipal Waste Model.100 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.101 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 12-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

35% 

3.2% 

0.0% 

32% 

3.2% 

91% 

73% 

6.2% 

0.0% 

67% 

6.2% 

92% 

38% 

2.9% 

0.0% 

35% 

2.9% 

0.7% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. The Czech Republic has chosen Method 2 to calculate the country’s performance against the WFD target of 
50%, which is met, but can be achieved by only recycling 29% of all municipal waste. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 4.6% 
and 8.1% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 

100 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
101 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

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115 

 
 
                                                   
 
of Appendix 2 of the Municipal Waste Model report.102 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Czech Republic is 40% 
(i.e. the amount of additional recycling that will have to be collected in 2030 to move from 
Full Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

12.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 12-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Czech Republic the figures show that if inputs to residual waste treatment 
plants were maintained as under the Full Implementation scenario, the total waste collected 
for recycling would be limited to 46%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 7-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 12-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

0% 

53% 

53% 

47% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 12-5). This is a simplifying assumption of the model. In reality, more waste 

102 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
  
                                                   
 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 12-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

0 

3,293 

748 

4,041 

68% 

0 

1,370 

311 

1,681 

33% 

0 

-1,923 

-437 

-2,360 

-35% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

12.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.103  Table 12-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 12-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

244 

19 

0 

0 

-244 

-19 

103 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

117 

 
 
 
                                                   
 
Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

1,322 

461 

0 

94 

-1,322 

-367 

0 

1,799 

1,799 

Source: European Reference Model on Municipal Waste Management. 

12.3 

Financial Costs 

12.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 12-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 12-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

101.3 

64 

36 

Labour Costs 

Mean Net Annual Earnings 

37,613 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

21 

26 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

71,062 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

5.0 

5.0 

Days between 
collections 

Eunomia 

Eunomia 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

6.3 

7.5 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 12-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 56 

€ 126 

€ 5 

€ 2 

€ 189 

€ 126 

€ 87 

€ 47 

€ 20 

€ 280 

€ 70 

-€ 39 

€ 42 

€ 18 

€ 91 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

12.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.104 By way of summary, the calculated costs for different waste 

104 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 

28/05/2015 

119 

 
 
 
 
                                                   
 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Czech Republic are shown in Table 12-9. 

Table 12-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 59.76 

€ 40.81 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

12.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 12-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                                                                                                                              
 
Table 12-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 280 

€ 186 

€ 466 

€ 189 

€ 305 

€ 494 

€ 91 

-€ 118 

-€ 27 

Source: European Reference Model on Municipal Waste Management. 

12.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.105 A number of the key country 
specific assumptions which have been made are shown in Table 12-11. 

Table 12-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

1 

59 

33 

1 

6 

% 

% 

% 

% 

% 

482 

Kg CO2 eq / MWh 

Marginal Heat Mix 

24 

68 

2 

2 

% 

% 

% 

% 

105 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

121 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

4 

263 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 

The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.106 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 12-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 12-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

  Open Air Composting 
n
o
i
t
s
e
g
i
D

In-Vessel Composting 

AD - Electricity Only 

€ 0 

-€ 10,703 

-€ 10,703 

-€ 66,061 

-€ 98,112 

-€ 32,050 

€ 1,794 

€ 6,248 

€ 4,454 

€ 1,432 

€ 5,597 

€ 4,165 

-€ 24 

-€ 191 

-€ 167 

106 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Electricity Only 

€ 11,695 

€ 867 

-€ 10,828 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Landfill 

€ 47,664 

€ 30,332 

-€ 17,332 

Collection and Sorting 

€ 3 

€ 6 

€ 2 

Total 

-€ 3,497 

-€ 65,956 

-€ 62,459 

Source: European Reference Model on Municipal Waste Management. 

12.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 12-1 and Table 12-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 

28/05/2015 

123 

 
 
 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 5.6 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 12-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

-€100-€90-€80-€70-€60-€50-€40-€30-€20-€10€0€1020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 12-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

-€ 3 

-€ 66 

-€ 62 

€ 0.1 

-€ 0.1 

-€ 0.24 

Financial Costs (social metric) 

€ 494 

€ 466 

-€ 27 

€ 5.2 

€ 5.2 

-€ 0.07 

Net Costs and Benefits 

€ 490 

€ 400 

-€ 90 

€ 5.4 

€ 5.1 

-€ 0.31 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Czech Republic 
depends on the amount of waste that is processed within the country’s borders as opposed 
to being exported for treatment abroad. The estimated increase in direct employment in 
2030 under the 70% recycling scenario is 1.8 thousand FTEs. Note that this is direct 
employment only with no provision for multiplier effects.

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13.0  Denmark 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.107 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
13-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.108 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.109 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.2 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

107 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
108 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
109 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with around one fifth of the benefit coming from reduced environmental 
externalities and three quarters from reduced financial costs.  

Table 13-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)110 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.04 

-€ 0.12 

-€ 0.17 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

13.1  Waste Generation and Management Projections 

Information was provided by the Danish Environment Protection Agency, via return of a 
detailed questionnaire which was specifically developed to gather the required input data 
for the model.111 Additional sources of information were obtained directly from reports and 
publications referred by the Danish Authorities. 

110 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
111 Environment Ministry. Danish Environment Protection Agency. Miljøministeriet. Miljøstyrelsen.  

28/05/2015 

127 

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

13.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 13-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.112  

The MSW generation projections are based on projections performed by the Danish 
Environmental Protection Agency’s using the FRIDA model. 113 MSW arisings are estimated 
to increase 1% per year until 2030 and 0% until 2050. The details of these projections are 
discussed in the technical documentation which accompanies the Municipal Waste 
Model.114 Interested readers should refer to this documentation for further details.  

Table 13-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

4,001 

4,139 

4,300 

4,481 

4,682 

Full Implementation Scenario (a) 

4,001 

4,139 

4,300 

4,481 

4,682 

70% Recycling Target Scenario (b) 

4,001 

4,139 

4,300 

4,462 

4,653 

Difference (b – a) 

0 

0 

0 

-18 

-29 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 

112 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
113 Danish EPA (2011). Waste Statistics 2009. Projection of waste 2011-2050. [In Danish] Affaldsstatistik 2009 
og Fremskrivning af affaldsmængder 2011-2050. Ref No Nr. 4 2011. Copenhagen, Denmark. 79 pp. 
114 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Denmark, the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.115 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Denmark’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

13.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 13-3. It is interesting to note 
that Denmark has chosen to calculate the Waste Framework Directive recycling target of 
50% by means of calculation method 1, which the model estimates at 57%. However, the 
model suggests that the total MSW recycling rate in 2020 (e.g. method 4) would be higher 
than the target (52%), suggesting Denamrk would meet the target even if method 4 had 
been selected.  

115 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

129 

 
                                                   
 
Table 13-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

57% 

5.7% 

0.0% 

51% 

5.7% 

90% 

77% 

7.5% 

0.0% 

69% 

7.5% 

90% 

20% 

1.9% 

0.0% 

18% 

1.9% 

0.1% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 5.4% 
and 7.5% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.116 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Denmark is 18% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

13.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 13-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 

116 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
                                                   
 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Denmark the figures show that if inputs to residual waste treatment plants 
were maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 60%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 13-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 13-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

0% 

40% 

40% 

60% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 13-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 13-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

0 

1,870 

140 

2,011 

46% 

0 

997 

75 

1,072 

29% 

0 

-873 

-65 

-939 

-18% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

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131 

 
  
 
 
13.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.117  Table 13-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 13-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

14 

465 

203 

0 

0 

0 

16 

665 

0 

0 

-14 

-449 

462 

Source: European Reference Model on Municipal Waste Management. 

13.3 

Financial Costs 

13.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 13-7 shows some of the key waste collection assumptions 
used in the modelling.  

117 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
Table 13-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

153.3 

72 

28 

Labour Costs 

Mean Net Annual Earnings 

38,244 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

35 

13 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

73,313 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

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133 

 
 
Table 13-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 199 

€ 143 

€ 22 

€ 4 

€ 368 

€ 226 

€ 114 

€ 32 

€ 10 

€ 382 

€ 27 

-€ 30 

€ 10 

€ 6 

€ 13 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

13.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.118 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Denmark are shown in Table 13-9. 

118 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                   
 
Table 13-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 52.91 

€ 74.68 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

13.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 13-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 13-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 382 

€ 178 

€ 560 

€ 368 

€ 237 

€ 606 

€ 13 

-€ 59 

-€ 46 

Source: European Reference Model on Municipal Waste Management. 

13.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.119 A number of the key country 
specific assumptions which have been made are shown in Table 13-11. 

119 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

135 

 
                                                   
 
Table 13-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

5 

91 

0 

4 

0 

% 

% 

% 

% 

% 

772 

Kg CO2 eq / MWh 

Marginal Heat Mix 

28 

26 

5 

20 

21 

% 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

178 

Kg CO2 eq / MWh 

25 

14 

42 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.120 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 13-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 13-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 0 

-€ 3,373 

-€ 3,373 

-€ 37,078 

-€ 47,723 

-€ 10,645 

€ 5,459 

€ 8,243 

€ 2,784 

€ 5,163 

€ 7,666 

€ 2,503 

-€ 21 

-€ 6 

€ 38 

€ 8 

-€ 44 

-€ 12 

€ 80 

€ 16 

-€ 23 

-€ 6 

€ 42 

€ 8 

Electricity Only 

-€ 134 

-€ 1,914 

-€ 1,779 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

€ 6,882 

€ 4,030 

-€ 2,852 

120 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

137 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 2 

€ 3 

€ 0 

Total 

-€ 19,688 

-€ 33,028 

-€ 13,340 

Source: European Reference Model on Municipal Waste Management. 

13.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 13-1 and Table 13-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 0.5 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

 
Figure 13-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 13-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

-€ 20 

-€ 33 

-€ 13 

-€ 0.2 

-€ 0.3 

-€ 0.04 

Financial Costs (social metric) 

€ 606 

€ 560 

-€ 46 

€ 6.8 

€ 6.7 

-€ 0.12 

Net Costs and Benefits 

€ 586 

€ 527 

-€ 59 

€ 6.6 

€ 6.4 

-€ 0.17 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Denmark depends 
on the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 

28/05/2015 

139 

-€60-€50-€40-€30-€20-€10€0€1020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
the 70% recycling scenario is 0.9 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects.

 
14.0  Estonia 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.121 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
14-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.122 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.123 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.05 billion (in 2014 real term prices) over the period from 2014-2030 in net 

121 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
122 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
123 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

141 

 
                                                   
 
present value terms, with just under half of the benefit coming from reduced environmental 
externalities and just over half from reduced financial costs.  

Table 14-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)124 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.02 

€ 0.00 

-€ 0.02 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

14.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Estonia with a meeting 
held in the Estonian Ministry of Environment, with participants from the Ministry, the 
Estonian Environment Information Centre (now being the Estonian Environment Agency) 
and a private institution.125 In addition, further information was gathered via a detailed 

124 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
125 CRI (2013, June 7th) Notes from meeting in Estonia with the Ministry of Environment and the Estonian 
Environment Information Centre, including additional feedback received after the visit.   

 
 
                                                   
 
questionnaire which was specifically developed to gather the required input data for the 
model.  

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

14.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 14-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.126  

For the period to 2020 MSW generation projections are based on Estonia’s own projection 
for this period. For the period from 2020 onwards a 1% annual increase in MSW arisings is 
assumed. The details of these projections are discussed in the technical documentation 
which accompanies the Municipal Waste Model.127 Interested readers should refer to this 
documentation for further details.  

Table 14-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

416 

458 

520 

547 

574 

Full Implementation Scenario (a) 

70% Recycling Target Scenario (b) 

Difference (b – a) 

416 

416 

0 

458 

458 

0 

524 

524 

0 

551 

548 

-3 

578 

574 

-4 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 

126 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
127 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

143 

 
                                                   
 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Estonia, the waste prevention impacts of PAYT and separate food waste collections 
are similar to the volume of additional garden waste collected, resulting in no net increase 
in waste arisings under the 70% recycling scenario. Further details on garden waste 
collections can be found in Section 4.5.3 of Appendix 5 which accompanies the European 
Municipal Waste Model.128 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.129 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Estonia’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.  

14.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

128 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
129 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
The key figures for the two scenarios in 2030 are given in Table 14-3. It is important to note 
that our understanding is that Estonaia has chosen to meet the 50% recycling target by 
means of calculation method 2. Given the nature of this calculation method the country will 
be able to achieve the target by recycling 33% of the total municipal waste stream (see Full 
Implementation scenario in the table below which assumes full compliance with the Waste 
Framework Directive target by the county’s chosen calculation method). The 33% overall 
recycling rate is based on the waste composition data and the projected municipal waste 
arisings that are saved in the Municipal Waste Model.130 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.131 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 14-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

35% 

2.9% 

0.3% 

33% 

2.6% 

92% 

74% 

6.3% 

0.1% 

68% 

6.2% 

92% 

39% 

3.4% 

-0.2% 

36% 

3.5% 

-0.8% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Estonia has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, which 
is met, but can be achieved by only recycling 33% of all municipal waste. 

130 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
131 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

145 

 
 
                                                   
 
Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 3.9% 
and 8.1% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.132 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Estonia is 35% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

14.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 14-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Estonia the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 69%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 14-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 14-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

8% 

23% 

31% 

69% 

132 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
  
                                                   
 
The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 14-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 14-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

46 

133 

196 

375 

66% 

18 

52 

77 

147 

31% 

-28 

-80 

-119 

-227 

-36% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

14.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.133  Table 14-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 14-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

30 

0 

-30 

133 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

147 

 
 
 
                                                   
 
Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

2 

203 

71 

0 

0 

0 

7 

-2 

-203 

-64 

284 

284 

Source: European Reference Model on Municipal Waste Management. 

14.3 

Financial Costs 

14.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 14-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 14-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

94.4 

51 

49 

Labour Costs 

Mean Net Annual Earnings 

9,998 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

16 

26 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Mean Gross Annual Earnings 

17,065 

€ 

Eurostat 

Collection Frequencies 

Food Waste Collection 

5.0  Days between 

Eunomia 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

6.3 

7.5 

collections 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 14-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 6 

€ 13 

€ 1 

€ 1 

€ 21 

€ 15 

€ 9 

€ 6 

€ 3 

€ 33 

€ 8 

-€ 4 

€ 5 

€ 2 

€ 11 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

14.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 

28/05/2015 

149 

 
 
 
 
Management Model.134 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Estonia are shown in Table 14-9. 

Table 14-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 44.61 

€ 27.53 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

14.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 14-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 14-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

million € 

134 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 33 

€ 19 

€ 51 

€ 21 

€ 30 

€ 52 

Source: European Reference Model on Municipal Waste Management. 

14.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.135 A number of the key country 
specific assumptions which have been made are shown in Table 14-11. 

Table 14-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

2 

0 

0 

89 

9 

541 

42 

0 

26 

31 

Marginal Heat Mix 

€ 11 

-€ 12 

-€ 1 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

135 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

151 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

0 

151 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.136 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 14-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 14-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

-€ 137 

-€ 625 

-€ 488 

-€ 3,307 

-€ 5,437 

-€ 2,130 

€ 529 

€ 85 

€ 0 

€ 0 

€ 1,652 

€ 1,123 

€ 135 

€ 0 

€ 0 

€ 51 

€ 0 

€ 0 

136 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 608 

€ 212 

-€ 396 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 458 

€ 155 

-€ 303 

€ 0 

€ 61 

€ 0 

€ 0 

€ 0 

€ 13 

€ 0 

€ 0 

€ 0 

-€ 48 

€ 0 

€ 0 

Landfill 

€ 7,571 

€ 3,152 

-€ 4,419 

Collection and Sorting 

€ 0 

€ 0 

€ 0 

Total 

€ 5,868 

-€ 743 

-€ 6,610 

Source: European Reference Model on Municipal Waste Management. 

14.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 14-1 and Table 14-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

28/05/2015 

153 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 0.8 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 14-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

-€8-€7-€6-€5-€4-€3-€2-€1€0€1€220112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 14-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

€ 6 

€ 52 

€ 58 

-€ 1 

€ 51 

€ 51 

-€ 7 

-€ 1 

-€ 7 

€ 0.0 

€ 0.6 

€ 0.0 

-€ 0.02 

€ 0.6 

€ 0.00 

€ 0.6 

€ 0.6 

-€ 0.02 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Estonia depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 0.3 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects.

28/05/2015 

155 

 
 
15.0  Finland 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.137 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
15-1Table 7-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.138 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.139 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

137 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
138 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
139 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
 
                                                   
 
For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.1 billion (in 2014 real term prices) over the period from 2014-2030 in net present 
value terms, with around two thirds of the benefit coming from reduced environmental 
externalities and one third from reduced financial costs.  

Table 15-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)140 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.03 

-€ 0.02 

-€ 0.06 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

15.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Finland with meetings 
held with the Finnish Ministry of Environment, Statistical office and the Finnish Environment 

140 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

28/05/2015 

157 

 
 
                                                   
 
Institute (SYKE).141 In addition, further information was gathered via a detailed 
questionnaire which was specifically developed to gather the required input data for the 
model.  

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

15.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 15-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.142  

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. 2007) and Bakas et al. (2011).143,144 The details of 
these projections are discussed in the technical documentation which accompanies the 
Municipal Waste Model.145 Interested readers should refer to this documentation for 
further details.  

Table 15-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

Full Implementation Scenario (a) 

70% Recycling Target Scenario (b) 

Difference (b – a) 

2,546 

2,649 

2,784 

2,926 

3,075 

2,546 

2,546 

0 

2,649 

2,649 

0 

2,773 

2,773 

0 

2,915 

2,902 

-13 

3,064 

3,046 

-18 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

141 CRI (2013, June 3rd) Notes from meeting in Finland with Finnish Ministry of Environment, Statistical office 
and SYKE., including additional feedback received after the visit.   
142 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
143 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
144 Bakas, I., Sieck, M., Hermann, T., Andersen, F. M. and Larsen, H. (2011). Projections of Municipal Waste 
Management and Greenhouse Gases. Prepared by Bakas et al., 89 pp. Copenhagen, Denmark 
145 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Finland, the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the two scenarios. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.146 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Finland’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

15.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 15-3. Finland has chosen to 
calculate the Waste Framework Directive recycling target of 50% by means of calculation 
method 4. This is equivalent to the Total MSW Recycling Rate figure below (50%). 

146 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

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Table 15-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

56% 

6.3% 

0.0% 

50% 

6.3% 

89% 

73% 

8.0% 

0.0% 

65% 

8.0% 

89% 

17% 

1.8% 

0.0% 

15% 

1.8% 

0.2% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 6.3% 
and 8.8% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.147 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Finland is 20% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

15.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 15-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 

147 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
                                                   
 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Finland the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 70%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 79% (Table 15-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 15-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

1% 

26% 

28% 

72% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 15-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

45 

802 

490 

1,336 

48% 

27 

488 

298 

813 

33% 

-17 

-314 

-192 

-523 

-15% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

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15.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.148  Table 15-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 15-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

19 

728 

492 

0 

0 

0 

10 

0 

0 

-19 

-718 

1,228 

737 

Source: European Reference Model on Municipal Waste Management. 

15.3 

Financial Costs 

15.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 15-7 shows some of the key waste collection assumptions 
used in the modelling.  

148 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
Table 15-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

150.2 

40 

60 

Labour Costs 

Mean Net Annual Earnings 

35,921 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

18 

21 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

59,194 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

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163 

 
 
Table 15-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 187 

€ 94 

€ 21 

€ 7 

€ 309 

€ 208 

€ 80 

€ 30 

€ 12 

€ 329 

€ 20 

-€ 14 

€ 9 

€ 5 

€ 20 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

15.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.149 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Finland are shown in Table 15-9. 

149 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                   
 
Table 15-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 42.09 

€ 35.78 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

15.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 15-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 15-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 329 

€ 136 

€ 465 

€ 309 

€ 167 

€ 476 

€ 20 

-€ 32 

-€ 12 

Source: European Reference Model on Municipal Waste Management. 

15.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.150 A number of the key country 
specific assumptions which have been made are shown in Table 15-11. 

150 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

165 

 
                                                   
 
Table 15-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

0 

100 

0 

0 

0 

% 

% 

% 

% 

% 

800 

Kg CO2 eq / MWh 

Marginal Heat Mix 

25 

35 

8 

27 

5 

% 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

183 

Kg CO2 eq / MWh 

25 

23 

65 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.151 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 15-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 15-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

-€ 1,128 

-€ 2,888 

-€ 1,760 

-€ 31,864 

-€ 38,386 

-€ 6,522 

€ 679 

€ 896 

€ 217 

€ 3,888 

€ 5,102 

€ 1,214 

€ 0 

-€ 180 

€ 508 

€ 92 

-€ 0 

€ 0 

-€ 252 

€ 699 

€ 128 

-€ 0 

€ 0 

-€ 72 

€ 191 

€ 36 

€ 0 

-€ 18,553 

-€ 13,612 

€ 4,941 

-€ 16,034 

-€ 11,635 

€ 4,399 

€ 0 

€ 0 

€ 0 

€ 0 

€ 525 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 309 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

-€ 215 

€ 0 

Landfill 

€ 27,085 

€ 18,559 

-€ 8,526 

151 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

167 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 1 

€ 2 

€ 0 

Total 

-€ 34,981 

-€ 41,076 

-€ 6,095 

Source: European Reference Model on Municipal Waste Management. 

15.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 15-1 and Table 15-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 0.7 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

 
Figure 15-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 15-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

-€ 35 

-€ 41 

-€ 6 

-€ 0.2 

-€ 0.2 

-€ 0.03 

Financial Costs (social metric) 

€ 476 

€ 465 

-€ 12 

€ 5.1 

€ 5.1 

-€ 0.02 

Net Costs and Benefits 

€ 441 

€ 424 

-€ 18 

€ 5.0 

€ 4.9 

-€ 0.06 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Finland depends on 
the amount of waste that is processed within the country’s borders as opposed to being 

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169 

-€20-€18-€16-€14-€12-€10-€8-€6-€4-€2€0€220112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 0.8 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects.

 
16.0  France 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.152 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
16-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.153 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.154 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €5.2 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

152 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
153 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
154 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

171 

 
                                                   
 
value terms, with around half of the benefit coming from reduced environmental 
externalities and half from reduced financial costs.  

Table 16-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)155 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 3.06 

-€ 2.24 

-€ 5.30 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

16.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to France with meetings 
held with the French Ministry of Ecology and Sustainable Development of Energy156 and the 
French Environmental Agency (ADEME).157 In addition, further information was gathered via 

155 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
156 Ministère de L'écologie du Développement Durable et de L'énergie 
157 CRI (2013, June 17th) Notes from meeting in France with Ministry of environment and ADEME, including 
additional feedback received after the visit.   

 
 
                                                   
 
a detailed questionnaire which was specifically developed to gather the required input data 
for the model.  

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

16.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 16-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.158 

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. (2007) and Bakas et al. (2011).159,160 The details of 
these projections are discussed in the technical documentation which accompanies the 
Municipal Waste Model.161 Interested readers should refer to this documentation for 
further details. 

Table 16-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

34,920 

36,458 

37,368 

37,865 

38,486 

Full Implementation Scenario (a) 

34,920 

36,458 

37,368 

37,865 

38,486 

70% Recycling Target Scenario (b) 

34,920 

36,458 

37,368 

37,522 

37,997 

Difference (b – a) 

0 

0 

0 

-343 

-488 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

158 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
159 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
160 Bakas, I., Sieck, M., Hermann, T., Andersen, F. M. and Larsen, H. (2011). Projections of Municipal Waste 
Management and Greenhouse Gases. Prepared by Bakas et al., 89 pp. Copenhagen, Denmark 
161 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

173 

 
                                                   
 
The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of France, the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.162 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for France’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.    

16.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 16-3. It is important to note 
that France has chosen to meet the 50% recycling target by means of calculation method 2. 
Given the nature of this calculation method the country will be able to achieve the target by 

162 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
recycling 39% of the total municipal waste stream (see Full Implementation scenario in the 
table below which assumes full compliance with the Waste Framework Directive target by 
the county’s chosen calculation method). The 39% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.163 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.164 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 16-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

42% 

3.5% 

0.2% 

39% 

3.3% 

92% 

77% 

7.3% 

0.1% 

69% 

7.2% 

91% 

35% 

3.8% 

-0.1% 

31% 

3.9% 

-1.6% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. France has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, which is 
met, but can be achieved by only recycling 39% of all municipal waste. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 3.9% 
and 8.0% respectively more waste needs to be collected than the overall recycling rate to 

163 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
164 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

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175 

 
 
                                                   
 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.165 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for France is 31% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

16.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 16-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For France the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 60%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 7-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 16-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

4% 

35% 

39% 

61% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 

165 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
  
                                                   
 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 16-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

1,539 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

13,469 

7,312 

22,320 

60% 

611 

5,343 

2,901 

8,854 

29% 

-929 

-8,126 

-4,411 

-13,465 

-31% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

16.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.166  Table 16-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 16-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

0 

0 

0 

0 

0 

0 

166 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

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Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

2,993 

4,101 

0 

-2,993 

125 

-3,976 

0 

6,969 

6,969 

Source: European Reference Model on Municipal Waste Management. 

16.3 

Financial Costs 

16.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 16-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 16-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

117.9 

54.4 

46 

Labour Costs 

Mean Net Annual Earnings 

32,115 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

18 

33 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

65,894 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

5.0 

5.0 

Days between 
collections 

Eunomia 

Eunomia 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

6.3 

7.5 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 16-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication cost 

Total Cost 

€ 1,650 

€ 1,317 

€ 172 

€ 16 

€ 3,155 

€ 1,962 

€ 915 

€ 314 

€ 127 

€ 3,317 

€ 313 

-€ 402 

€ 141 

€ 111 

€ 162 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

16.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.167 By way of summary, the calculated costs for different waste 

167 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 

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179 

 
 
 
 
                                                   
 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in France are shown in Table 16-9. 

Table 16-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 39.34 

€ 51.15 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

16.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 16-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                                                                                                                              
 
Table 16-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

€ 3,155 

€ 2,193 

€ 5,348 

million € 

€ 3,317 

€ 1,435 

€ 4,752 

€ 162 

-€ 757 

-€ 595 

Source: European Reference Model on Municipal Waste Management. 

16.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.168 A number of the key country 
specific assumptions which have been made are shown in Table 16-11. 

Table 16-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

4 

5 

78 

2 

10 

70 

61 

10 

16 

0 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Marginal Heat Mix 

168 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

181 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

13 

212 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.169 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 16-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 16-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

€ 0 

-€ 99,925 

-€ 99,925 

-€ 272,729 

-€ 583,741 

-€ 311,011 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

€ 0 

€ 0 

€ 0 

In-Vessel Composting 

€ 56,935 

€ 81,079 

€ 24,144 

AD - Electricity Only 

AD - CHP 

€ 613 

€ 85 

€ 1,308 

€ 182 

€ 694 

€ 97 

169 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 365 

€ 44 

€ 707 

€ 101 

€ 342 

€ 57 

Electricity Only 

€ 475,644 

€ 246,648 

-€ 228,995 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

AD based MBT 

€ 27,087 

€ 8,028 

-€ 19,058 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

Landfill 

€ 338,839 

€ 154,607 

-€ 184,231 

Collection and Sorting 

€ 18 

€ 34 

€ 16 

Total 

€ 626,901 

-€ 190,971 

-€ 817,872 

Source: European Reference Model on Municipal Waste Management. 

16.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 16-1 and Table 16-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

28/05/2015 

183 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 47.1 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 16-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

-€1,600-€1,400-€1,200-€1,000-€800-€600-€400-€200€0€20020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 16-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 627 

-€ 191 

-€ 818 

€ 6.3 

€ 3.2 

-€ 3.06 

Financial Costs (social metric) 

€ 5,348 

€ 4,752 

-€ 595 

€ 60.2 

€ 58.0 

-€ 2.24 

Net Costs and Benefits 

€ 5,974 

€ 4,562 

-€ 1,413 

€ 66.5 

€ 61.2 

-€ 5.30 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in France depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 25.4 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects.

28/05/2015 

185 

 
17.0  Germany 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.170 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
17-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.171 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.172 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.6 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

170 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
171 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
172 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with around one third of the benefit coming from reduced environmental 
externalities and two thirds from reduced financial costs.  

Table 17-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)173 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.15 

-€ 0.32 

-€ 0.47 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

17.1  Waste Generation and Management Projections 

Information was provided by the German Federal Environment Agency, via return of a 
detailed questionnaire which was specifically developed to gather the required input data 
for the model. 

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

173 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

28/05/2015 

187 

 
 
                                                   
 
17.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 17-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.174  

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. (2007) and Bakas et al. (2011).175,176 The details of 
these projections are discussed in the technical documentation which accompanies the 
Municipal Waste Model.177 Interested readers should refer to this documentation for 
further details. 

Table 17-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

49,185 

48,978 

49,651 

49,403 

49,269 

Full Implementation Scenario (a) 

49,185 

48,978 

49,651 

49,403 

49,269 

70% Recycling Target Scenario (b) 

49,185 

48,978 

49,651 

49,403 

49,173 

Difference (b – a) 

0 

0 

0 

0 

-96 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 

174 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
175 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
176 Bakas, I., Sieck, M., Hermann, T., Andersen, F. M. and Larsen, H. (2011). Projections of Municipal Waste 
Management and Greenhouse Gases. Prepared by Bakas et al., 89 pp. Copenhagen, Denmark 
177 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Germany, the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.178 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Germany’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.     

17.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 7-3. Germany has chosen to 
calculate the Waste Framework Directive recycling target of 50% by means of calculation 
method 4. This is equivalent in approach to the Total MSW Recycling Rate figure below 
(61%). Therefore, Germany is exceeding the target. 

Table 17-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

178 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

189 

 
 
                                                   
 
Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

68% 

7.8% 

0.3% 

61% 

7.5% 

89% 

76% 

8.3% 

0.2% 

67% 

8.1% 

89% 

7% 

0.5% 

-0.1% 

6% 

0.6% 

0.2% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 8.1% 
and 9.2% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.179 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Germany is 9% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

17.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 17-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Germany the figures show that if inputs to residual waste treatment plants 
were maintained as under the Full Implementation scenario, the total waste collected for 

179 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
                                                   
 
recycling would be limited to 64%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 79% (Table 7-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 17-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

5% 

26% 

31% 

69% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 17-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 17-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

2,472 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Thousand tonnes 

1,913 

9,947 

153 

-559 

-2,909 

-45 

12,856 

198 

15,526 

12,012 

-3,513 

36% 

30% 

-6% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

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191 

 
  
 
17.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.180  Table 17-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 17-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1,674 

166 

-1,508 

7,631 

9,140 

1,508 

Source: European Reference Model on Municipal Waste Management. 

17.3 

Financial Costs 

17.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 17-7 shows some of the key waste collection assumptions 
used in the modelling.  

180 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
Table 17-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

135.6 

85 

15 

Labour Costs 

Mean Net Annual Earnings 

28,659 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

30 

21 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

58,987 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

28/05/2015 

193 

 
 
Table 17-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

Million € 

€ 2,536 

€ 1,154 

€ 332 

€ 54 

€ 4,076 

€ 2,522 

€ 1,222 

€ 299 

€ 26 

€ 4,069 

€ 14 

-€ 68 

€ 33 

€ 28 

€ 7 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

17.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.181 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Germany are shown in Table 17-9. 

181 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
                                                   
 
Table 17-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 55.08 

€ 60.22 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

17.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 17-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 17-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

€ 4,069 

€ 2,086 

€ 6,155 

million € 

€ 4,076 

€ 1,876 

€ 5,952 

€ 7 

-€ 210 

-€ 203 

Source: European Reference Model on Municipal Waste Management. 

17.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.182 A number of the key country 
specific assumptions which have been made are shown in Table 17-11. 

182 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

195 

 
                                                   
 
Table 17-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

13 

43 

23 

4 

16 

% 

% 

% 

% 

% 

420 

Kg CO2 eq / MWh 

Marginal Heat Mix 

Incinerator Generation Efficiencies 

49 

32 

2 

3 

14 

220 

25 

14 

42 

80 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.183 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 17-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 17-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

€ 0 

-€ 24,693 

-€ 24,693 

-€ 895,875 

-€ 941,360 

-€ 45,485 

Open Air Composting 

€ 66,977 

€ 78,210 

€ 11,233 

In-Vessel Composting 

€ 36,061 

€ 41,788 

€ 5,727 

AD - Electricity Only 

-€ 1,536 

-€ 1,815 

AD - CHP 

AD - Gas to Grid 

-€ 608 

-€ 719 

€ 1,563 

€ 1,831 

AD - Gas to Vehicle Fuel 

€ 441 

€ 523 

-€ 279 

-€ 110 

€ 268 

€ 82 

Electricity Only 

€ 32,142 

€ 2,413 

-€ 29,728 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 12,456 

€ 9,487 

-€ 2,969 

€ 0 

€ 745 

€ 0 

€ 0 

€ 274 

€ 0 

€ 0 

-€ 471 

€ 0 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Residual MRF + Combustion 

€ 4,710 

€ 849 

-€ 3,861 

Landfill 

€ 13,694 

€ 11,140 

-€ 2,554 

183 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

197 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 58 

€ 63 

€ 4 

Total 

-€ 729,172 

-€ 822,009 

-€ 92,836 

Source: European Reference Model on Municipal Waste Management. 

17.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 17-1 and Table 17-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 2.7 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

 
Figure 17-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 17-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

-€ 729 

-€ 822 

-€ 93 

-€ 7.9 

-€ 8.1 

-€ 0.15 

Financial Costs (social metric) 

€ 6,155 

€ 5,952 

-€ 203 

€ 72.1 

€ 71.8 

-€ 0.32 

Net Costs and Benefits 

€ 5,426 

€ 5,130 

-€ 296 

€ 64.2 

€ 63.7 

-€ 0.47 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Germany depends 
on the amount of waste that is processed within the country’s borders as opposed to being 

28/05/2015 

199 

-€300-€250-€200-€150-€100-€50€0€5020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 3.1 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects.

 
18.0  Greece 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.184 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
18-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.185 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.186 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.5 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

184 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
185 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
186 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

201 

 
                                                   
 
value terms, with around one third of the benefit coming from reduced environmental 
externalities and two thirds from reduced financial costs.  

Table 18-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)187 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.24 

€ 0.07 

-€ 0.16 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

18.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Greece with a meeting 
held with the representatives from Greek authorities (Ministry Of Environment, Ministry of 
Interior and National Waste Associations).188 In addition, further information was gathered 

187 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
188 CRI (June 2013) Notes from meeting in Greece with Greek authorities, including additional feedback 
received after the visit.   

 
 
                                                   
 
via a detailed questionnaire which was specifically developed to gather the required input 
data for the model.  

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

18.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 18-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.189  

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. (2007) and Bakas et al. (2011).190,191 The details of 
these projections are discussed in the technical documentation which accompanies the 
Municipal Waste Model.192 Interested readers should refer to this documentation for 
further details. 

Table 18-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

5,807 

5,468 

5,590 

5,644 

5,692 

Full Implementation Scenario (a) 

5,807 

5,468 

5,940 

5,995 

6,043 

70% Recycling Target Scenario (b) 

5,807 

5,468 

5,940 

5,993 

6,018 

Difference (b – a) 

0 

0 

0 

-2 

-25 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

189 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
190 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
191 Bakas, I., Sieck, M., Hermann, T., Andersen, F. M. and Larsen, H. (2011). Projections of Municipal Waste 
Management and Greenhouse Gases. Prepared by Bakas et al., 89 pp. Copenhagen, Denmark 
192 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

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The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Greece, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.193 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.194 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Greece’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

18.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

193 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
194 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 18-3. It is important to note 
that Greece has chosen to meet the 50% recycling target by means of calculation method 2. 
Given the nature of this calculation method the country will be able to achieve the target by 
recycling 33% of the total municipal waste stream (see Full Implementation scenario in the 
table below which assumes full compliance with the Waste Framework Directive target by 
the county’s chosen calculation method). The 33% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.195 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.196 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 18-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

34% 

2.8% 

1.5% 

33% 

1.2% 

96% 

75% 

5.7% 

0.6% 

70% 

5.2% 

93% 

41% 

3.0% 

-0.9% 

37% 

3.9% 

-3.3% 

195 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
196 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

205 

 
 
                                                   
 
Full 
Implementation 

70% Recycling 
Target 

Difference 

Note:  

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Greece has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, which 
is met, but can be achieved by only recycling 33% of all municipal waste. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 2.6% 
and 7.7% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.197 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Greece is 35% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

18.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 18-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Greece the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 50%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 18-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 18-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

52% 

Full Implementation 

197 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
  
                                                   
 
Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

0% 

52% 

48% 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 18-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 18-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

3,163 

1,201 

-1,962 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

0 

800 

3,963 

67% 

0 

304 

1,504 

30% 

0 

-496 

-2,459 

-37% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

18.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.198  Table 7-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 

198 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

207 

 
  
 
                                                   
 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 18-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

270 

264 

839 

256 

0 

0 

0 

51 

-270 

-264 

-839 

-204 

0 

1,179 

1,179 

Source: European Reference Model on Municipal Waste Management. 

18.3 

Financial Costs 

18.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 18-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 18-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

113.3 

47 

53 

Labour Costs 

Mean Net Annual Earnings 

17,700 

Tax rate (% of salary) 

16 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

 
 
Assumption 

Value 

Unit 

Source 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

23 

% 

Eurostat 

Mean Gross Annual Earnings 

29,145 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

1.7 

1.4 

2.5 

3.8 

Average days 
between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Collection Frequencies 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 18-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 226 

€ 271 

€ 12 

€ 12 

€ 520 

€ 383 

€ 143 

€ 47 

€ 31 

€ 605 

€ 157 

-€ 127 

€ 35 

€ 20 

€ 85 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

28/05/2015 

209 

 
 
 
18.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.199 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Greece are shown in Table 18-9. 

Table 18-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 62.91 

€ 0.00 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

18.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 18-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

199 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Table 18-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 605 

€ 180 

€ 784 

€ 520 

€ 270 

€ 791 

Source: European Reference Model on Municipal Waste Management. 

18.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.200 A number of the key country 
specific assumptions which have been made are shown in Table 18-11. 

Table 18-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

18 

56 

0 

13 

14 

598 

Kg CO2 eq / MWh 

Marginal Heat Mix 

0 

99 

1 

0 

% 

% 

% 

% 

€ 85 

-€ 91 

-€ 6 

% 

% 

% 

% 

% 

200 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

211 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

0 

300 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.201 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 18-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 18-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

-€ 9,483 

-€ 16,168 

-€ 6,684 

-€ 33,401 

-€ 55,133 

-€ 21,731 

€ 5,680 

€ 10,380 

€ 4,700 

€ 2,250 

€ 11,407 

€ 9,157 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

201 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 35,814 

€ 11,714 

-€ 24,100 

Biodrying with no Plastics Recycling 

€ 0 

€ 0 

€ 0 

Biodrying with Plastics Recycling 

€ 12,204 

€ 4,205 

-€ 7,999 

AD based MBT 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

€ 43,584 

€ 27,420 

-€ 16,164 

Collection and Sorting 

€ 2 

€ 3 

€ 1 

Total 

€ 56,649 

-€ 6,172 

-€ 62,821 

Source: European Reference Model on Municipal Waste Management. 

18.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 18-1 and Table 18-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

28/05/2015 

213 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 6.3 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 18-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 18-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

-€70-€60-€50-€40-€30-€20-€10€0€10€20€3020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 57 

-€ 6 

-€ 63 

€ 0.6 

€ 0.4 

-€ 0.24 

Financial Costs (social metric) 

€ 791 

€ 784 

-€ 6 

Net Costs and Benefits 

€ 847 

€ 778 

-€ 69 

Source: European Reference Model on Municipal Waste Management. 

€ 8.2 

€ 8.8 

€ 8.2 

€ 0.07 

€ 8.6 

-€ 0.16 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Greece depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 2.1 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

28/05/2015 

215 

 
 
 
 
19.0  Hungary 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.202 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
19-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.203 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.204 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.5 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

202 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
203 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
204 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with around 60% of the benefit coming from reduced environmental 
externalities and 40% from reduced financial costs.  

Table 19-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)205 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.38 

€ 0.07 

-€ 0.31 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

19.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Hungary with meetings 
held with the Hungarian Ministry of Rural Development (responsible for environmental 
issues), the National Waste Management Agency (OHÜ) and the National Institute for 
Environment (NEKI).206 In addition, further information was gathered via a detailed 

205 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
206 CRI (2013, May 30th) Notes from meeting in Hungary with the Hungarian Ministry of Rural Development, 
OHÜ and NEKI, including additional feedback received after the visit.   

28/05/2015 

217 

 
 
                                                   
 
questionnaire which was specifically developed to gather the required input data for the 
model.  

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

19.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 7-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.207  

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. (2007) and Bakas et al. (2011).208,209 The details of 
these projections are discussed in the technical documentation which accompanies the 
Municipal Waste Model.210 Interested readers should refer to this documentation for 
further details. 

Table 19-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

4,087 

4,302 

4,462 

4,552 

4,674 

Full Implementation Scenario (a) 

4,087 

4,302 

4,609 

4,697 

4,818 

70% Recycling Target Scenario (b) 

4,087 

4,302 

4,609 

4,697 

4,801 

Difference (b – a) 

0 

0 

0 

0 

-17 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

207 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
208 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
209 Bakas, I., Sieck, M., Hermann, T., Andersen, F. M. and Larsen, H. (2011). Projections of Municipal Waste 
Management and Greenhouse Gases. Prepared by Bakas et al., 89 pp. Copenhagen, Denmark 
210 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Hungary, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.211 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.212 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for X’s MSW stream is presented in Table 2 of the accompanying 
Member State Data Table.   

19.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

211 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
212 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

219 

 
                                                   
 
2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 19-3. It is important to note 
that Hungary has chosen to meet the 50% recycling target by means of calculation method 
2. Given the nature of this calculation method the country will be able to achieve the target 
by recycling 31% of the total municipal waste stream (see Full Implementation scenario in 
the table below which assumes full compliance with the Waste Framework Directive target 
by the county’s chosen calculation method). The 31% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.213 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.214 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 19-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

33% 

2.8% 

0.8% 

31% 

2.0% 

94% 

76% 

6.6% 

0.3% 

69% 

6.3% 

92% 

43% 

3.8% 

-0.5% 

38% 

4.3% 

-2.3% 

213 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
214 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
Full 
Implementation 

70% Recycling 
Target 

Difference 

Note:  

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Hungary has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, which 
is met, but can be achieved by only recycling 31% of all municipal waste. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 2.4% 
and 5.9% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.215 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Hungary is 36% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

19.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 19-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Hungary the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 69%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 76% (Table 7-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 19-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

21% 

Full Implementation 

215 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

221 

 
 
  
                                                   
 
Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

13% 

34% 

66% 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 19-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 19-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

1,003 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

627 

1,606 

3,236 

69% 

363 

227 

581 

1,172 

30% 

-640 

-400 

-1,024 

-2,064 

-38% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

19.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.216  Table 19-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 

216 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
  
 
                                                   
 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 19-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

219 

407 

668 

174 

0 

0 

0 

0 

14 

997 

-219 

-407 

-668 

-160 

997 

Source: European Reference Model on Municipal Waste Management. 

19.3 

Financial Costs 

19.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 19-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 19-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

Labour Costs 

Mean Net Annual Earnings 

Tax rate (% of salary) 

140.9 

68 

32 

7,474 

24 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

28/05/2015 

223 

 
 
Assumption 

Value 

Unit 

Source 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

26 

% 

Eurostat 

Mean Gross Annual Earnings 

14,773 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Collection Frequencies 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 19-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 45 

€ 126 

€ 0 

€ 4 

€ 176 

€ 106 

€ 97 

€ 24 

€ 21 

€ 247 

€ 60 

-€ 30 

€ 24 

€ 16 

€ 71 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

 
 
 
19.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.217 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Hungary are shown in Table 19-9. 

Table 19-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 62.70 

€ 40.05 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

19.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 19-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

217 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

225 

 
                                                   
 
Table 19-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 247 

€ 118 

€ 365 

€ 176 

€ 192 

€ 368 

Source: European Reference Model on Municipal Waste Management. 

19.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.218 A number of the key country 
specific assumptions which have been made are shown in Table 19-11. 

Table 19-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

30 

18 

44 

5 

2 

293 

Kg CO2 eq / MWh 

Marginal Heat Mix 

76 

13 

6 

2 

% 

% 

% 

% 

€ 71 

-€ 74 

-€ 3 

% 

% 

% 

% 

% 

218 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

3 

211 

% 

Kg CO2 eq / MWh 

Incinerator Generation Efficiencies 

25 

16.4 

49 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.219 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 19-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 19-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

-€ 7,184 

-€ 19,635 

-€ 12,451 

-€ 36,850 

-€ 75,241 

-€ 38,392 

€ 2,104 

€ 6,916 

€ 4,812 

€ 1,424 

€ 3,949 

€ 2,526 

€ 92 

€ 10 

€ 397 

€ 43 

€ 305 

€ 33 

219 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

227 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 104 

€ 14 

€ 398 

€ 65 

€ 294 

€ 51 

Electricity Only 

€ 13,715 

€ 5,657 

-€ 8,058 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 1,451 

€ 393 

-€ 1,058 

Biodrying with no Plastics Recycling 

€ 0 

€ 0 

€ 0 

Biodrying with Plastics Recycling 

€ 16,319 

€ 5,732 

-€ 10,587 

AD based MBT 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

€ 64,016 

€ 27,570 

-€ 36,445 

Collection and Sorting 

€ 3 

€ 5 

€ 2 

Total 

€ 55,219 

-€ 43,751 

-€ 98,970 

Source: European Reference Model on Municipal Waste Management. 

19.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 19-1 and Table 7-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 8.5 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 19-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 19-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

28/05/2015 

229 

-€120-€100-€80-€60-€40-€20€0€20€4020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 55 

-€ 44 

-€ 99 

€ 0.6 

€ 0.2 

-€ 0.38 

Financial Costs (social metric) 

€ 368 

€ 365 

-€ 3 

Net Costs and Benefits 

€ 423 

€ 322 

-€ 102 

Source: European Reference Model on Municipal Waste Management. 

€ 4.1 

€ 4.6 

€ 4.1 

€ 0.07 

€ 4.3 

-€ 0.31 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Hungary depends 
on the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 3.3 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

 
 
 
 
20.0 

Ireland 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.220 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
20-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.221 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.222 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.3 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

220 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
221 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
222 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

231 

 
                                                   
 
value terms, with around 40% of the benefit coming from reduced environmental 
externalities and 60% from reduced financial costs.  

Table 20-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)223 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.13 

-€ 0.19 

-€ 0.32 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

20.1  Waste Generation and Management Projections 

Information was provided by Ireland’s Environmental Protection Agency (EPA), via return of 
a detailed questionnaire which was specifically developed to gather the required input data 
for the model. 

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

223 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

 
 
                                                   
 
20.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 20-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.224  

The MSW generation projections are based on projections performed by the Economic and 
Social Research Institute (ESRI), on behalf of the Ireland Environmental Protection Agency, 
using the Sustainable Development Model for Ireland (ISus).225 MSW arisings are expected 
to remain static until 2016 and then increase by approximately 830,000 tonnes per year 
thereafter. Further details of these projections are discussed in the technical documentation 
which accompanies the Municipal Waste Model.226 Interested readers should refer to this 
documentation for further details.  

Table 20-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

2,823 

2,823 

3,060 

3,357 

3,653 

Full Implementation Scenario (a) 

2,823 

2,823 

3,060 

3,357 

3,653 

70% Recycling Target Scenario (b) 

2,823 

2,823 

3,060 

3,343 

3,625 

Difference (b – a) 

0 

0 

0 

-14 

-28 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 

224 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
225 Economic and Social Research Institute (2013) Ireland's Sustainable Development Model (ISus), Date 
Accessed: 15 October 2013, Available at: www.esri.ie/research/research_areas/environment/isus/  
226 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

233 

 
                                                   
 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Ireland, the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.227 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Ireland’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

20.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 7-3. It is interesting to note 
that Ireland has chosen to calculate the Waste Framework Directive recycling target of 50% 
by means of calculation method 1, which the model estimates at 69%. However, the model 
suggests that the total MSW recycling rate in 2020 (e.g. method 4) would be higher than the 
target (50%), suggesting Ireland would meet the target even if method 4 had been selected.  

227 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
 
                                                   
 
Table 20-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

56% 

6.1% 

0.8% 

51% 

5.3% 

91% 

78% 

8.3% 

0.5% 

70% 

7.8% 

90% 

22% 

2.2% 

-0.3% 

19% 

2.5% 

-0.6% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 5.8% 
and 8.2% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.228 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Ireland is 20% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

20.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 20-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 

228 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

235 

 
 
                                                   
 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Ireland the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 59%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 20-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 20-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

33% 

6% 

39% 

61% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 20-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 20-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

1,221 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

205 

178 

1,604 

48% 

612 

103 

89 

805 

29% 

-608 

-102 

-89 

-799 

-19% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

 
  
 
20.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.229  Table 20-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 20-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

3 

37 

12 

0 

0 

0 

1 

52 

0 

0 

-3 

-36 

40 

Source: European Reference Model on Municipal Waste Management. 

20.3 

Financial Costs 

20.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 20-7 shows some of the key waste collection assumptions 
used in the modelling.  

229 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

237 

 
 
 
 
 
                                                   
 
Table 20-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

164.3 

52 

48 

Labour Costs 

Mean Net Annual Earnings 

40,722 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

6 

14 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

51,221 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

 
 
 
 
Table 20-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 198 

€ 124 

€ 13 

€ 0 

€ 334 

€ 197 

€ 96 

€ 19 

€ 4 

€ 316 

-€ 1 

-€ 28 

€ 6 

€ 4 

-€ 18 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

20.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.230 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Ireland are shown in Table 20-9. 

230 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

239 

 
 
                                                   
 
Table 20-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 84.25 

€ 28.28 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

20.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 20-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 20-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 316 

€ 107 

€ 423 

€ 334 

€ 145 

€ 480 

-€ 18 

-€ 38 

-€ 56 

Source: European Reference Model on Municipal Waste Management. 

20.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.231 A number of the key country 
specific assumptions which have been made are shown in Table 20-11. 

231 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                   
 
Table 20-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Marginal Heat Mix 

43 

30 

0 

0 

28 

410 

27 

18 

51 

4 

0 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

236 

Kg CO2 eq / MWh 

25 

17.5 

42 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

28/05/2015 

241 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.232 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 20-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 20-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 0 

-€ 4,567 

-€ 4,567 

-€ 37,105 

-€ 60,591 

-€ 23,485 

€ 1,553 

€ 2,765 

€ 1,212 

€ 1,689 

€ 2,975 

€ 1,286 

€ 196 

€ 614 

€ 418 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Electricity Only 

€ 5,532 

€ 4,768 

-€ 764 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Biodrying with Plastics Recycling 

€ 19,715 

€ 9,798 

-€ 9,918 

AD based MBT 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

€ 12,580 

€ 9,839 

-€ 2,742 

232 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 2 

€ 2 

€ 0 

Total 

€ 4,549 

-€ 34,590 

-€ 39,140 

Source: European Reference Model on Municipal Waste Management. 

20.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 20-1 and Table 20-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 4.9 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

28/05/2015 

243 

 
Figure 20-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 20-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 4 

-€ 34 

-€ 38 

€ 0.0 

-€ 0.1 

-€ 0.13 

Financial Costs (social metric) 

€ 480 

€ 423 

-€ 56 

€ 5.0 

€ 4.8 

-€ 0.19 

Net Costs and Benefits 

€ 484 

€ 389 

-€ 95 

€ 5.0 

€ 4.7 

-€ 0.32 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Ireland depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 

-€100-€90-€80-€70-€60-€50-€40-€30-€20-€10€020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
the 70% recycling scenario is 1.8 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

28/05/2015 

245 

 
  
 
 
21.0 

Italy 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.233 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 7-1 
shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.234 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.235 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €4.4 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

233 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
234 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
235 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with just under half of the benefit coming from reduced environmental 
externalities and just over half from reduced financial costs.  

Table 21-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)236 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 2.36 

-€ 3.25 

-€ 5.61 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

21.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Italy with meetings held 
with the Italian Environmental Protection Agency (ISPRA). 237 In addition, further information 
was gathered via a detailed questionnaire which was specifically developed to gather the 

236 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
237 CRI (2013, July 1st) Notes from meeting in Italy with ISPRA, including additional feedback received after the 
visit.   

28/05/2015 

247 

 
 
                                                   
 
required input data for the model. Information was also provided through a booklet/report 
on waste from cities and municipalities. 238 

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

21.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 21-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.239  

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. (2007) and Bakas et al. (2011.240,241 The details of 
these projections are discussed in the technical documentation which accompanies the 
Municipal Waste Model.242 

Table 21-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

33,046 

35,313 

37,025 

38,238 

39,023 

Full Implementation Scenario (a) 

33,046 

35,313 

37,025 

38,238 

39,023 

70% Recycling Target Scenario (b) 

33,046 

35,313 

37,025 

37,967 

38,662 

Difference (b – a) 

0 

0 

0 

-271 

-361 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

238 ISPRA (2013) ”Rapporto Rifiuti Urbani Edizione 2013 – Estratto” report nr 176 
239 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
240 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
241 Bakas, I., Sieck, M., Hermann, T., Andersen, F. M. and Larsen, H. (2011). Projections of Municipal Waste 
Management and Greenhouse Gases. Prepared by Bakas et al., 89 pp. Copenhagen, Denmark 
242 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Italy, the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.243 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Italy’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

21.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 21-3. It is important to note 
that Italy has chosen to meet the 50% recycling target by means of calculation method 2. 
Given the nature of this calculation method the country will be able to achieve the target by 

243 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

249 

 
                                                   
 
recycling 40% of the total municipal waste stream (see Full Implementation scenario in the 
table below which assumes full compliance with the Waste Framework Directive target by 
the county’s chosen calculation method). The 40% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.244 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.245 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 21-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

43% 

4.2% 

1.1% 

40% 

3.1% 

93% 

74% 

7.6% 

0.5% 

67% 

7.1% 

90% 

31% 

3.4% 

-0.6% 

27% 

4.0% 

-2.4% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 
2. Italy has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, which is 
met, but can be achieved by only recycling 40% of all municipal waste. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 3.3% 
and 8.1% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 

244 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
245 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.246 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Italy is 30% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

21.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 21-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Italy the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 61%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 7-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 21-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

29% 

9% 

38% 

62% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 

246 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

251 

 
  
                                                   
 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 21-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

11,446 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

3,552 

7,105 

22,104 

59% 

5,144 

1,597 

3,193 

9,934 

32% 

-6,302 

-1,956 

-3,912 

-12,170 

-27% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

21.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.247  Table 7-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 21-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

0 

0 

0 

0 

0 

0 

247 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
 
                                                   
 
Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

2,443 

5,101 

0 

16 

-2,443 

-5,085 

356 

7,884 

7,528 

Source: European Reference Model on Municipal Waste Management. 

21.3 

Financial Costs 

21.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 21-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 21-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

100.0 

88 

12 

Labour Costs 

Mean Net Annual Earnings 

26,155 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

21 

29 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

52,041 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

1.7 

1.4 

Days between 
collections 

Eunomia 

Eunomia 

28/05/2015 

253 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

2.5 

3.8 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 21-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 1,167 

€ 1,226 

€ 191 

€ 26 

€ 2,610 

€ 1,608 

€ 534 

€ 147 

€ 120 

€ 2,409 

€ 441 

-€ 691 

-€ 44 

€ 94 

-€ 200 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

21.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.248 By way of summary, the calculated costs for different waste 

248 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 

 
 
 
                                                   
 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Italy are shown in Table 21-9. 

Table 21-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 90.04 

€ 72.44 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

21.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 21-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

255 

 
                                                                                                                                                              
 
Table 21-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

€ 3,055 

€ 1,610 

€ 4,665 

million € 

€ 2,775 

€ 1,146 

€ 3,921 

-€ 280 

-€ 464 

-€ 744 

Source: European Reference Model on Municipal Waste Management. 

21.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.249 A number of the key country 
specific assumptions which have been made are shown in Table 21-11. 

Table 21-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

50 

15 

0 

10 

25 

% 

% 

% 

% 

% 

380 

Kg CO2 eq / MWh 

Marginal Heat Mix 

58 

1 

35 

3 

% 

% 

% 

% 

249 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

3 

211 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.250 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 21-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 21-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

€ 0 

-€ 91,857 

-€ 91,857 

-€ 410,395 

-€ 677,974 

-€ 267,579 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

€ 28,499 

€ 59,155 

€ 30,656 

In-Vessel Composting 

€ 20,595 

€ 39,327 

€ 18,731 

AD - Electricity Only 

€ 1,164 

€ 2,699 

€ 1,534 

AD - CHP 

€ 123 

€ 284 

€ 160 

250 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

257 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

€ 1,978 

€ 4,353 

€ 2,375 

AD - Gas to Vehicle Fuel 

€ 253 

€ 614 

€ 362 

Electricity Only 

€ 70,313 

€ 42,944 

-€ 27,369 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 120,638 

€ 46,844 

-€ 73,795 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

AD based MBT 

€ 69,377 

€ 26,874 

-€ 42,503 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

€ 405,460 

€ 246,547 

-€ 158,914 

Collection and Sorting 

€ 22 

€ 33 

€ 11 

Total 

€ 308,030 

-€ 300,158 

-€ 608,188 

Source: European Reference Model on Municipal Waste Management. 

21.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 21-1  

and Table 21-13. From this it is clear that there is a net benefit to be gained from moving 
towards higher recycling rates (this is shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 

 
 
 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 46.5 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 21-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 21-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

28/05/2015 

259 

-€1,600-€1,400-€1,200-€1,000-€800-€600-€400-€200€0€20020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 308 

-€ 300 

-€ 608 

€ 2.9 

€ 0.5 

-€ 2.36 

Financial Costs (social metric) 

€ 4,665 

€ 3,921 

-€ 744 

€ 51.9 

€ 48.7 

-€ 3.25 

Net Costs and Benefits 

€ 4,973 

€ 3,621 

-€ 1,352 

€ 54.8 

€ 49.2 

-€ 5.61 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Italy depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 19.0 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

 
  
 
 
22.0  Latvia 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.251 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
22-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.252 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.253 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.03 billion (in 2014 real term prices) over the period from 2014-2030 in net 

251 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
252 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
253 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

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present value terms, with around 60% of the benefit coming from reduced environmental 
externalities and 40% from reduced financial costs.  

Table 22-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)254 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.02 

-€ 0.00 

-€ 0.02 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

22.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Latvia with meetings 
held with representatives of the Ministry of Environmental Protection and Regional 
Development and the Latvian Environment, Geology and Meteorology Centre (LEGMC). In 

254 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

 
 
                                                   
 
addition, further information was gathered via a detailed questionnaire which was 
specifically developed to gather the required input data for the model. 255 

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

22.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 7-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.256  

MSW generation projections were taken from the 2012 European Topic Centre projection 
using the methodology as reported in Andersen et al. (2007).257 The details of these 
projections are discussed in the technical documentation which accompanies the Municipal 
Waste Model.258 Interested readers should refer to this documentation for further details. 

Table 22-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

Full Implementation Scenario (a) 

70% Recycling Target Scenario (b) 

Difference (b – a) 

983 

983 

983 

0 

983 

983 

983 

0 

983 

983 

983 

1,013 

1,012 

1,011 

1,013 

1,009 

1,006 

0 

-4 

-6 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

255 Ministry of Environmental Protection and Regional Development (2013) Questionnaire Information 
Returned Following Meetings With Eunomia on May 16th 2013 in Latvia, 16 May 2013 
256 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
257 Andersen, F. M., Larsen, H., Skovgaard, M., Moll, S. and Isoard, S. (2007) A European Model for Waste and 
Material ﬂows, Resources, Conservation and Recycling, Vol.49, pp. 421–435 
258 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

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The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Latvia, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.259 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.260 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Latvia’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.     

22.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

259 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
260 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 22-3. Information made 
available to Eunomia suggested that Latvia has chosen to calculate the Waste Framework 
Directive recycling target of 50% by means of calculation method 4. This is equivalent to the 
Total MSW Recycling Rate figure below (50%). 

Table 22-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

52% 

3.8% 

1.4% 

50% 

2.5% 

95% 

75% 

5.5% 

0.8% 

70% 

4.8% 

94% 

22% 

1.7% 

-0.6% 

20% 

2.3% 

-1.7% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 3.4% 
and 6.4% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.261 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Latvia is 20% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 

261 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

265 

 
 
                                                   
 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

22.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 22-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Latvia the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 66%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 76% (Table 22-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 22-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

34% 

0% 

34% 

66% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 22-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 22-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

348 

0 

133 

481 

50% 

184 

0 

70 

254 

30% 

-164 

0 

-63 

-227 

-20% 

 
  
 
Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

22.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.262  Table 22-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 22-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

27 

326 

112 

0 

0 

0 

9 

0 

0 

-27 

-317 

456 

344 

Source: European Reference Model on Municipal Waste Management. 

22.3 

Financial Costs 

22.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 22-7 shows some of the key waste collection assumptions 
used in the modelling.  

262 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

267 

 
 
 
                                                   
 
Table 22-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

98.1 

49 

51 

Labour Costs 

Mean Net Annual Earnings 

5,995 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

29 

20 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

11,659 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

 
 
 
 
Table 22-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communication Cost 

Total Cost 

€ 12 

€ 16 

€ 6 

€ 3 

€ 37 

€ 14 

€ 13 

€ 9 

€ 5 

€ 41 

€ 2 

-€ 3 

€ 3 

€ 2 

€ 4 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

22.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.263 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Latvia are shown in Table 22-9. 

263 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

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269 

 
 
                                                   
 
Table 22-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 
Revenue from Heat Sales 

€ 68.82 
€ 37.36 

€ per MWh 
€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

22.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 22-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 22-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 41 

€ 25 

€ 66 

€ 37 

€ 30 

€ 67 

€ 4 

-€ 6 

-€ 1 

Source: European Reference Model on Municipal Waste Management. 

22.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.264 A number of the key country 
specific assumptions which have been made are shown in Table 22-11. 

Table 22-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

264 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                   
 
Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

100 

0 

0 

0 

0 

% 

% 

% 

% 

% 

400 

Kg CO2 eq / MWh 

Marginal Heat Mix 

Incinerator Generation Efficiencies 

1 

16 

0 

81 

1 

54 

25 

14 

42 

80 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

28/05/2015 

271 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.265 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 22-12. Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 22-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

-€ 1,463 

-€ 2,300 

-€ 837 

-€ 8,741 

-€ 11,235 

-€ 2,494 

€ 1,189 

€ 1,781 

€ 1,023 

€ 1,513 

€ 593 

€ 489 

€ 0 

€ 0 

€ 0 

€ 0 

-€ 1 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

-€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Residual MRF + Combustion 

€ 5,835 

€ 3,055 

-€ 2,779 

Landfill 

€ 6,948 

€ 4,998 

-€ 1,951 

265 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 0 

€ 0 

€ 0 

Total 

€ 4,791 

-€ 2,188 

-€ 6,979 

Source: European Reference Model on Municipal Waste Management. 

22.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 22-1 and Table 22-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 0.5 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

28/05/2015 

273 

 
Figure 22-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 22-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

€ 5 

€ 67 

€ 72 

-€ 2 

€ 66 

€ 64 

-€ 7 

-€ 1 

-€ 8 

€ 0.1 

€ 0.8 

€ 0.1 

-€ 0.02 

€ 0.8 

-€ 0.00 

€ 0.9 

€ 0.8 

-€ 0.02 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Latvia depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 

-€9-€8-€7-€6-€5-€4-€3-€2-€1€0€120112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
the 70% recycling scenario is 0.3 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

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275 

 
  
 
 
23.0  Lithuania 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.266 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
23-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.267 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.268 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.1 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

266 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
267 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
268 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with around half of the benefit coming from reduced environmental 
externalities and half from reduced financial costs.  

Table 23-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)269 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.08 

€ 0.06 

-€ 0.02 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

23.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Lithuania with a meeting 
held with the Waste Department of the Lithuanian Ministry of Environment. In addition, 
further information was gathered via a detailed questionnaire, filled in by the Ministry’s 
consultants Ekokonsultacijos, which was specifically developed to gather the required input 
data for the model. Additional data and clarifications were obtained from Rasa Uselyte, the 
Chief Desk Officer from the Waste Prevention and Management Strategy Division. 

269 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

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The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

23.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 23-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.270  

The MSW generation projections are based on the Lithuanian Ministry’s projections. The 
projections for waste arisings are always uncertain, but the Ministry’s projections of around 
0.5% per annum are not excessive and therefore are considered plausible. Further details of 
these projections are discussed in the technical documentation which accompanies the 
Municipal Waste Model.271 Interested readers should refer to this documentation for 
further details. 

Table 23-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

1,367 

1,378 

1,401 

1,401 

1,401 

Full Implementation Scenario (a) 

1,367 

1,378 

1,401 

1,401 

1,401 

70% Recycling Target Scenario (b) 

1,367 

1,378 

1,401 

1,422 

1,419 

Difference (b – a) 

0 

0 

0 

22 

19 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 

270 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
271 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Lithuania, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the 70% recycling scenario. Further details on garden waste 
collections can be found in Section 4.5.3 of Appendix 5 which accompanies the European 
Municipal Waste Model.272 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.273 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Lithuania’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

23.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

272 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
273 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

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The key figures for the two scenarios in 2030 are given in Table 7-3. It is important to note 
that Lithuania has chosen to meet the 50% recycling target by means of calculation method 
2. Given the nature of this calculation method the country will be able to achieve the target 
by recycling 28% of the total municipal waste stream (see Full Implementation scenario in 
the table below which assumes full compliance with the Waste Framework Directive target 
by the county’s chosen calculation method). The 28% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.274 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.275 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 23-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

32% 

3.0% 

-0.7% 

28% 

3.7% 

88% 

72% 

5.9% 

-0.9% 

65% 

6.9% 

90% 

41% 

2.9% 

-0.2% 

37% 

3.2% 

2.2% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Lithuania has chosen Method 2 to calculate the country’s performance against the WFD target of 28%, 
which is met, but can be achieved by only recycling 29% of all municipal waste. 

274 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
275 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 4.0% 
and 8.7% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.276 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Lithuania is 44% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

23.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 7-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Lithuania the figures show that if inputs to residual waste treatment plants 
were maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 58%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 79% (Table 23-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 23-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

32% 

6% 

38% 

62% 

276 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

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The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 23-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

442 

88 

430 

959 

72% 

183 

36 

178 

397 

34% 

-259 

-51 

-252 

-563 

-37% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

23.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.277  Table 23-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 23-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

207 

0 

-207 

277 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
 
                                                   
 
Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

533 

286 

0 

0 

0 

0 

96 

-533 

-286 

96 

551 

551 

Source: European Reference Model on Municipal Waste Management. 

23.3 

Financial Costs 

23.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 23-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 23-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

99.2 

42 

58 

Labour Costs 

Mean Net Annual Earnings 

6,049 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

17 

28 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Mean Gross Annual Earnings 

11,071 

€ 

Eurostat 

Collection Frequencies 

Food Waste Collection 

5.0  Days between 

Eunomia 

28/05/2015 

283 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

6.3 

7.5 

collections 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 23-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 6 

€ 27 

€ 2 

€ 1 

€ 36 

€ 23 

€ 23 

€ 19 

€ 6 

€ 71 

€ 17 

-€ 5 

€ 17 

€ 6 

€ 36 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

23.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 

 
 
 
Management Model.278 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Lithuania are shown in Table 23-9. 

Table 23-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 71.73 

€ 37.92 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

23.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 23-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 23-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

million € 

278 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

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Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 71 

€ 33 

€ 105 

€ 36 

€ 57 

€ 93 

Source: European Reference Model on Municipal Waste Management. 

23.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.279 A number of the key country 
specific assumptions which have been made are shown in Table 23-11. 

Table 23-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

60 

0 

0 

11 

28 

306 

Kg CO2 eq / MWh 

Marginal Heat Mix 

18 

0 

0 

55 

% 

% 

% 

% 

€ 36 

-€ 24 

€ 12 

% 

% 

% 

% 

% 

279 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

27 

77 

% 

Kg CO2 eq / MWh 

Incinerator Generation Efficiencies 

25 

16.4 

48 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.280 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 23-1. Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 23-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

€ 0 

-€ 2,682 

-€ 2,682 

-€ 6,449 

-€ 15,046 

-€ 8,597 

€ 763 

€ 3,032 

€ 2,269 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

280 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

287 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 1,447 

€ 787 

-€ 659 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 1,806 

€ 701 

-€ 1,105 

€ 0 

€ 1,494 

€ 1,486 

€ 707 

€ 0 

€ 649 

€ 586 

€ 300 

€ 0 

-€ 845 

-€ 900 

-€ 407 

Landfill 

€ 16,776 

€ 8,980 

-€ 7,796 

Collection and Sorting 

€ 1 

€ 1 

€ 0 

Total 

€ 18,030 

-€ 2,692 

-€ 20,722 

Source: European Reference Model on Municipal Waste Management. 

23.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 7-1 and Table 7-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 2.5 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 23-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

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289 

-€25-€20-€15-€10-€5€0€5€10€1520112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 23-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

Financial Costs (social metric) 

€ 18 

€ 93 

€ 105 

-€ 3 

-€ 21 

Net Costs and Benefits 

€ 111 

€ 102 

€ 0.2 

€ 1.0 

€ 1.2 

€ 0.1 

-€ 0.08 

€ 1.0 

€ 0.06 

€ 1.1 

-€ 0.02 

€ 12 

-€ 9 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Lithuania depends 
on the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 0.7 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

 
  
 
 
24.0  Luxembourg 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.281 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
24-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.282 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.283 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.02 billion (in 2014 real term prices) over the period from 2014-2030 in net 

281 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
282 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
283 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

291 

 
                                                   
 
present value terms, with just under half of the benefit coming from reduced environmental 
externalities and just over half from reduced financial costs.  

Table 24-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)284 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.01 

-€ 0.01 

-€ 0.02 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

24.1  Waste Generation and Management Projections 

Information was provided by the Environment Agency of Luxembourg, via return of a 
detailed questionnaire which was specifically developed to gather the required input data 
for the model.285 Additional sources of information were obtained directly from reports and 
publications referred to in the completed questionnaire by the Authorities. 

284 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
285 Le Gouvernement du Grand Duché de Luxembourg. Ministère du Développement Durable. Administration 
de l’Environnement.  

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

24.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 24-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.286  

MSW generation projections assume an increase in waste generated of 1% per year. The 
details of these projections are discussed in the technical documentation which 
accompanies the Municipal Waste Model.287 Interested readers should refer to this 
documentation for further details.  

Table 24-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

Full Implementation Scenario (a) 

70% Recycling Target Scenario (b) 

Difference (b – a) 

365 

365 

365 

0 

389 

389 

389 

0 

421 

421 

421 

0 

449 

449 

448 

-1 

477 

477 

475 

-2 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 

286 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
287 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

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293 

 
                                                   
 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Luxembourg, the waste prevention impacts of PAYT result in a net reduction in 
waste arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.288 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Luxembourgs’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

24.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 24-3. It is important to note 
that Luxembourg has chosen to meet the 50% recycling target by means of calculation 
method 3. The overall recycling rate is based on the waste composition data and the 
projected municipal waste arisings that are saved in the Municipal Waste Model. 289 

288 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 
289 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
                                                   
 
Table 24-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

60% 

5.3% 

0.1% 

55% 

5.2% 

91% 

77% 

6.8% 

0.1% 

70% 

6.8% 

91% 

17% 

1.6% 

0.0% 

15% 

1.6% 

-0.2% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 5.4% 
and 7.0% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.290 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Luxembourg is 16% (i.e. 
the amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

24.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 24-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 

290 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

295 

 
 
                                                   
 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Luxembourg the figures show that if inputs to residual waste treatment plants 
were maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 62%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 77% (Table 24-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 24-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

8% 

27% 

35% 

65% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 24-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

39 

129 

24 

192 

43% 

23 

75 

14 

111 

29% 

-16 

-54 

-10 

-80 

-15% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

 
  
 
24.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.291  Table 24-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 24-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

0 

26 

19 

0 

0 

0 

1 

44 

0 

0 

0 

-25 

25 

Source: European Reference Model on Municipal Waste Management. 

24.3 

Financial Costs 

24.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 24-7 shows some of the key waste collection assumptions 
used in the modelling.  

291 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

297 

 
 
                                                   
 
Table 24-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

100.0 

80 

20 

Labour Costs 

Mean Net Annual Earnings 

48,294 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

15 

13 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

67,376 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

 
 
Table 24-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 18 

€ 11 

€ 5 

€ 0 

€ 34 

€ 19 

€ 9 

€ 7 

€ 1 

€ 36 

€ 1 

-€ 2 

€ 2 

€ 0 

€ 2 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

24.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.292 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Luxembourg are shown in Table 24-9. 

292 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

299 

 
 
                                                   
 
Table 24-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 62.45 

€ 51.44 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

24.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 24-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 24-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 36 

€ 17 

€ 53 

€ 34 

€ 23 

€ 57 

€ 2 

-€ 5 

-€ 4 

Source: European Reference Model on Municipal Waste Management. 

24.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.293 A number of the key country 
specific assumptions which have been made are shown in Table 24-11. 

Table 24-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

293 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
                                                   
 
Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

73 

0 

0 

2 

25 

304 

0 

0 

0 

100 

0 

1 

25 

14 

42 

80 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Marginal Heat Mix 

Incinerator Generation Efficiencies 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

28/05/2015 

301 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.294 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 24-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 24-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 0 

-€ 455 

-€ 5,577 

-€ 6,433 

€ 1,642 

€ 2,069 

€ 0 

€ 64 

€ 5 

€ 11 

€ 7 

€ 0 

€ 86 

€ 6 

€ 14 

€ 9 

-€ 455 

-€ 856 

€ 427 

€ 0 

€ 22 

€ 2 

€ 3 

€ 2 

Electricity Only 

€ 3,816 

€ 2,662 

-€ 1,154 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 533 

€ 293 

-€ 240 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

€ 1,310 

€ 912 

-€ 399 

294 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 0 

€ 1 

€ 0 

Total 

€ 1,811 

-€ 837 

-€ 2,647 

Source: European Reference Model on Municipal Waste Management. 

24.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 24-1 and Table 24-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 0.1 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

28/05/2015 

303 

 
Figure 24-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 24-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

€ 2 

€ 57 

€ 59 

-€ 1 

€ 53 

€ 52 

-€ 3 

-€ 4 

-€ 6 

€ 0.0 

€ 0.6 

€ 0.0 

-€ 0.01 

€ 0.6 

-€ 0.01 

€ 0.6 

€ 0.6 

-€ 0.02 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Luxembourg 
depends on the amount of waste that is processed within the country’s borders as opposed 

-€7-€6-€5-€4-€3-€2-€1€0€120112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
to being exported for treatment abroad. The estimated increase in direct employment in 
2030 under the 70% recycling scenario is 0.1 thousand FTEs. Note that this is direct 
employment only with no provision for multiplier effects. 

28/05/2015 

305 

 
  
 
 
25.0  Malta 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.295 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
25-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.296 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.297 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.02 billion (in 2014 real term prices) over the period from 2014-2030 in net 

295 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
296 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
297 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
present value terms, with around 40% of the benefit coming from reduced environmental 
externalities and 60% from reduced financial costs.  

Table 25-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)298 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.01 

€ 0.02 

€ 0.01 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

25.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Malta with meetings 
held with the Malta Environment & Planning Authority (MEPA), WasteServ Malta and the 
National Statistics Office.299 In addition, MEPA provided additional information via return of 

298 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
299 Eunomia (2013, June 3rd) Notes from meeting in Malta with MEPA, WasteServ Malta and the National 
Statistics Office.   

28/05/2015 

307 

 
 
                                                   
 
a questionnaire which was specifically developed to gather the required input data for the 
model.300  

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

25.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 25-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.301  

The MSW generation projections are based on various projections carried out by the Malta 
Environment and Planning Authority (MEPA). The details of these projections are discussed 
in the technical documentation which accompanies the Municipal Waste Model.302 
Interested readers should refer to this documentation for further details.  

Table 25-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

Full Implementation Scenario (a) 

70% Recycling Target Scenario (b) 

Difference (b – a) 

243 

243 

243 

0 

252 

252 

252 

0 

262 

275 

275 

0 

271 

284 

285 

1 

282 

295 

295 

0 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 

300 MEPA (2013) Questionnaire information returned following meetings with Eunomia on June 3 rd 2013 in 
Malta. 
301 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
302 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Malta, the waste prevention impacts of separate food waste collections are lower 
than the volume of additional garden waste collected, resulting in a net increase in waste 
arisings under the two scenarios. Further details on garden waste collections can be found 
in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste Model.303 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.304 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Malta’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.     

25.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

303 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
304 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

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The key figures for the two scenarios in 2030 are given in Table 25-3. It is important to note 
that Malta has chosen to meet the 50% recycling target by means of calculation method 1. 
Given the nature of this calculation method the country will be able to achieve the target by 
recycling 33% of the total municipal waste stream (see Full Implementation scenario in the 
table below which assumes full compliance with the Waste Framework Directive target by 
the county’s chosen calculation method). The 33% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.305 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.306 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 25-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

34% 

2.7% 

1.2% 

33% 

1.5% 

96% 

75% 

5.7% 

0.4% 

70% 

5.2% 

93% 

41% 

2.9% 

-0.8% 

37% 

3.7% 

-2.5% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Malta has chosen Method 1 to calculate the country’s performance against the WFD target of 50%, which is 
met, but can be achieved by only recycling 33% of all municipal waste. 

305 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
306 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 3.3% 
and 7.4% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.307 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Malta is 31% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

25.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 7-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Malta the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 58%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 25-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 25-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

47% 

0% 

47% 

53% 

307 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

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The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 25-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

139 

0 

55 

193 

67% 

52 

0 

21 

73 

30% 

-86 

0 

-34 

-120 

-37% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

25.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.308  Table 25-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 25-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

8 

0 

-8 

308 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
 
                                                   
 
Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

13 

5 

1 

0 

0 

0 

1 

7 

-13 

-5 

-1 

7 

Source: European Reference Model on Municipal Waste Management. 

25.3 

Financial Costs 

25.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 25-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 25-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

180.1 

100 

0 

Labour Costs 

Mean Net Annual Earnings 

19,513 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

8 

9 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Mean Gross Annual Earnings 

23,593 

€ 

Eurostat 

Collection Frequencies 

Food Waste Collection 

1.7  Days between 

Eunomia 

28/05/2015 

313 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

1.4 

2.5 

3.8 

collections 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 25-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 11 

€ 14 

€ 0 

€ 0 

€ 26 

€ 21 

€ 8 

€ 1 

€ 1 

€ 31 

€ 10 

-€ 6 

€ 1 

€ 1 

€ 5 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

25.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 

 
 
 
Management Model.309 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Malta are shown in Table 25-9. 

Table 25-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 113.82 

€ 0.00 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

25.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 25-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 25-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

million € 

309 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

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Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 31 

€ 10 

€ 42 

€ 26 

€ 14 

€ 41 

Source: European Reference Model on Municipal Waste Management. 

25.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.310 A number of the key country 
specific assumptions which have been made are shown in Table 25-11. 

Table 25-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

100 

0 

0 

0 

0 

400 

Kg CO2 eq / MWh 

Marginal Heat Mix 

0 

0 

95 

2 

% 

% 

% 

% 

€ 5 

-€ 4 

€ 1 

% 

% 

% 

% 

% 

310 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

3 

242 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.311 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 25-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 25-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

-€ 355 

-€ 712 

-€ 357 

-€ 1,612 

-€ 2,735 

-€ 1,122 

€ 164 

€ 138 

€ 60 

€ 8 

€ 406 

€ 317 

€ 289 

€ 40 

€ 242 

€ 179 

€ 229 

€ 32 

311 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

317 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

Collection and Sorting 

Total 

€ 46 

€ 8 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 212 

€ 38 

€ 166 

€ 31 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 1,234 

€ 0 

€ 407 

€ 0 

-€ 827 

€ 0 

€ 2,902 

€ 1,649 

-€ 1,252 

€ 0 

€ 2,593 

€ 0 

-€ 88 

€ 0 

-€ 2,681 

Source: European Reference Model on Municipal Waste Management. 

25.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 25-1 and Table 25-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 0.3 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 25-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

28/05/2015 

319 

-€3-€2-€1€0€1€2€3€420112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 25-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

€ 3 

€ 41 

€ 43 

-€ 0 

€ 42 

€ 42 

-€ 3 

€ 1 

-€ 1 

€ 0.0 

€ 0.4 

€ 0.5 

€ 0.0 

-€ 0.01 

€ 0.5 

€ 0.02 

€ 0.5 

€ 0.01 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Malta depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 0.1 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

 
  
 
 
26.0  Netherlands 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.312 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
26-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.313 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.314 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.5 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

312 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
313 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
314 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

321 

 
                                                   
 
value terms, with just under half of the benefit coming from reduced environmental 
externalities and just over half from reduced financial costs.  

Table 26-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)315 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.17 

-€ 0.18 

-€ 0.35 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

26.1  Waste Generation and Management Projections 

Information was provided by a contact at the Department of Water, Transport and 
Environment (Water, Verkeer en Leefomgeving), via return of a detailed questionnaire 
which was specifically developed to gather the required input data for the model. Our 
contact was sent the country questionnaire and where necessary certain points were 
followed up to clarify issues and/or obtain further information. 

315 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

26.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 26-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.316  

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. (2007).317 This projection assumes a 0.25% annual 
grown in waste arisings between 2011 and 2015, an annual increase of 0.5% between 2015 
and 2020, and 1% year on year increase after that. The details of these projections are 
discussed in the technical documentation which accompanies the Municipal Waste 
Model.318 Interested readers should refer to this documentation for further details.  

Table 26-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

9,947 

10,047 

10,301 

10,826 

11,378 

Full Implementation Scenario (a) 

9,947 

10,047 

10,301 

10,826 

11,378 

70% Recycling Target Scenario (b) 

9,947 

10,047 

10,301 

10,798 

11,307 

Difference (b – a) 

0 

0 

0 

-28 

-71 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 

316 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
317 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
318 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

323 

 
                                                   
 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of the Netherlands, the waste prevention impacts of PAYT result in a net reduction in 
waste arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.319 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for the Netherlands’ MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

26.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 26-3. It is interesting to note 
that the Netherlands has chosen to calculate the Waste Framework Directive recycling 
target of 50% by means of calculation method 2, which the model estimates at 63%. 
However, the model suggests that the total MSW recycling rate in 2020 (e.g. method 4) 
would be higher than the target (55%), suggesting the Netherlands would meet the target 
even if method 4 had been selected.  

319 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
Table 26-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

60% 

5.3% 

0.7% 

55% 

4.6% 

92% 

76% 

7.1% 

0.3% 

69% 

6.7% 

91% 

16% 

1.7% 

-0.4% 

14% 

2.1% 

-1.2% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 4.0% 
and 6.9% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.320 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for the Netherlands is 18% 
(i.e. the amount of additional recycling that will have to be collected in 2030 to move from 
Full Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

26.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 26-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 

320 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

325 

 
 
                                                   
 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For the Netherlands the figures show that if inputs to residual waste treatment 
plants were maintained as under the Full Implementation scenario, the total waste collected 
for recycling would be limited to 55%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 77% (Table 26-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 26-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

11% 

28% 

39% 

61% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 26-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

1,209 

3,229 

114 

4,552 

42% 

720 

1,924 

68 

2,712 

29% 

-488 

-1,305 

-46 

-1,839 

-14% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

 
  
 
26.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.321  Table 26-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 26-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

15 

718 

617 

0 

0 

0 

16 

0 

0 

-15 

-702 

1,334 

717 

Source: European Reference Model on Municipal Waste Management. 

26.3 

Financial Costs 

26.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 26-7 shows some of the key waste collection assumptions 
used in the modelling.  

321 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

327 

 
 
                                                   
 
Table 26-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

108.6 

98 

2 

Labour Costs 

Mean Net Annual Earnings 

33,196 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

22 

23 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

59,659 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

 
 
 
 
Table 26-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 422 

€ 267 

€ 133 

€ 5 

€ 827 

€ 471 

€ 215 

€ 138 

€ 18 

€ 843 

€ 49 

-€ 52 

€ 5 

€ 13 

€ 15 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

26.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.322 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in the Netherlands are shown in Table 26-9. 

322 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

329 

 
 
                                                   
 
Table 26-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 53.22 

€ 49.73 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

26.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 26-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 26-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

€ 827 

€ 518 

€ 1,345 

million € 

€ 843 

€ 419 

€ 1,262 

€ 15 

-€ 99 

-€ 84 

Source: European Reference Model on Municipal Waste Management. 

26.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.323 A number of the key country 
specific assumptions which have been made are shown in Table 26-11. 

323 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                   
 
Table 26-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

61 

23 

4 

4 

8 

% 

% 

% 

% 

% 

452 

Kg CO2 eq / MWh 

Marginal Heat Mix 

77 

11 

4 

1 

7 

% 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

208 

Kg CO2 eq / MWh 

25 

20 

20 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

28/05/2015 

331 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.324 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 26-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 26-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

€ 0 

-€ 12,863 

-€ 12,863 

-€ 90,540 

-€ 129,328 

-€ 38,789 

Open Air Composting 

€ 16,384 

€ 21,906 

€ 5,523 

In-Vessel Composting 

€ 10,150 

€ 12,663 

€ 2,513 

AD - Electricity Only 

€ 252 

€ 501 

€ 248 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Electricity Only 

€ 45,167 

€ 29,381 

-€ 15,785 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Residual MRF + Combustion 

€ 12,394 

€ 6,950 

-€ 5,444 

Landfill 

€ 7,205 

€ 5,075 

-€ 2,130 

324 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 9 

€ 11 

€ 2 

Total 

€ 1,021 

-€ 65,705 

-€ 66,726 

Source: European Reference Model on Municipal Waste Management. 

26.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 26-1 and Table 26-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 3.0 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

28/05/2015 

333 

 
Figure 26-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 26-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 1 

-€ 66 

-€ 67 

€ 0.1 

-€ 0.1 

-€ 0.17 

Financial Costs (social metric) 

€ 1,345 

€ 1,262 

-€ 84 

€ 14.7 

€ 14.6 

-€ 0.18 

Net Costs and Benefits 

€ 1,346 

€ 1,196 

-€ 150 

€ 14.8 

€ 14.4 

-€ 0.35 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in the Netherlands 
depends on the amount of waste that is processed within the country’s borders as opposed 

-€160-€140-€120-€100-€80-€60-€40-€20€0€2020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
to being exported for treatment abroad. The estimated increase in direct employment in 
2030 under the 70% recycling scenario is 2.7 thousand FTEs. Note that this is direct 
employment only with no provision for multiplier effects. 

28/05/2015 

335 

 
  
 
 
27.0  Poland 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.325 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 7-1 
shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.326 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.327 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.6 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

325 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
326 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
327 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with around 40% of the benefit coming from reduced environmental 
externalities and 60% from reduced financial costs.  

Table 27-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)328 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.34 

€ 0.72 

€ 0.38 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

27.1  Waste Generation and Management Projections 

As part of the model development process visit was conducted to Poland with a meeting 
held with the representatives from Polish Authorities (Ministry of Environment, Chief 
Inspectorate for Environmental Protection). In addition, further information was gathered 
via a detailed questionnaire which was specifically developed to gather the required input 
data for the model. Additional information was retrieved by desktop research and from 
further EEA work on regional MSW management studies. 

328 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

28/05/2015 

337 

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

27.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 27-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.329  

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. (2007).330 The details of these projections are 
discussed in the technical documentation which accompanies the Municipal Waste 
Model.331 Interested readers should refer to this documentation for further details. 

Table 27-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

12,129 

12,417 

12,790 

13,022 

13,215 

Full Implementation Scenario (a) 

12,129 

12,417 

13,046 

13,275 

13,465 

70% Recycling Target Scenario (b) 

12,129 

12,417 

13,046 

13,276 

13,415 

Difference (b – a) 

0 

0 

0 

1 

-50 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 

329 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
330 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
331 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Poland, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.332 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.333 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Poland’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

27.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 27-3. It is important to note 
that Poland has chosen to meet the 50% recycling target by means of calculation method 2. 

332 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
333 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

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Given the nature of this calculation method the country will be able to achieve the target by 
recycling 32% of the total municipal waste stream (see Full Implementation scenario in the 
table below which assumes full compliance with the Waste Framework Directive target by 
the county’s chosen calculation method). The 32% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.334 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.335 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 27-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

33% 

2.8% 

2.1% 

32% 

0.7% 

98% 

75% 

6.3% 

0.7% 

70% 

5.6% 

93% 

42% 

3.5% 

-1.4% 

38% 

4.9% 

-5.4% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Poland has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, which 
is met, but can be achieved by only recycling 32% of all municipal waste. 

Source: European Reference Model on Municipal Waste Management. 

334 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
335 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
These figures show that, under the Full Implementation and 70% recycling scenarios, 1.4% 
and 6.4% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.336 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Poland is 36% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

27.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 27-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Poland the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 52%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 76% (Table 27-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 27-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

40% 

9% 

50% 

50% 

336 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

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The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 27-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 27-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

5,407 

1,267 

2,373 

9,046 

67% 

1,979 

464 

869 

3,312 

30% 

-3,427 

-803 

-1,504 

-5,734 

-38% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

27.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.337  Table 7-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 27-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

796 

0 

-796 

337 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
 
                                                   
 
Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

1,478 

3,518 

917 

0 

0 

63 

-1,478 

-3,518 

-854 

0 

5,276 

5,276 

Source: European Reference Model on Municipal Waste Management. 

27.3 

Financial Costs 

27.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 27-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 27-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

135.2 

58 

42 

Labour Costs 

Mean Net Annual Earnings 

8,468 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

22 

17 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Mean Gross Annual Earnings 

13,906 

€ 

Eurostat 

Collection Frequencies 

Food Waste Collection 

5.0  Days between 

Eunomia 

28/05/2015 

343 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

6.3 

7.5 

collections 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 27-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 308 

€ 379 

€ 30 

€ 25 

€ 742 

€ 543 

€ 298 

€ 134 

€ 83 

€ 1,057 

€ 235 

-€ 81 

€ 104 

€ 57 

€ 315 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

27.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 

 
 
 
Management Model.338 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details) 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Poland are shown in Table 27-9. 

Table 27-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 57.75 

€ 34.01 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

27.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 27-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 27-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

million € 

338 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

345 

 
                                                   
 
Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

Full Implementation 

70% Recycling Target 

Difference 

€ 742 

€ 513 

€ 1,256 

million € 

€ 1,057 

€ 295 

€ 1,352 

€ 315 

-€ 219 

€ 96 

Source: European Reference Model on Municipal Waste Management. 

27.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.339 A number of the key country 
specific assumptions which have been made are shown in Table 27-11. 

Table 27-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

0 

100 

0 

0 

0 

% 

% 

% 

% 

% 

800 

Kg CO2 eq / MWh 

Marginal Heat Mix 

4 

79 

9 

3 

% 

% 

% 

% 

339 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

5 

275 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.340 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 27-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 27-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

-€ 11,192 

-€ 36,801 

-€ 25,609 

Recycling 

-€ 93,385 

-€ 170,955 

-€ 77,570 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

€ 9,101 

€ 35,153 

€ 26,052 

€ 1,772 

€ 3,741 

€ 1,968 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

340 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

347 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Electricity Only 

-€ 13,938 

-€ 9,489 

€ 4,449 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Residual MRF + Combustion 

-€ 44,669 

-€ 22,222 

€ 22,447 

Landfill 

€ 108,348 

€ 58,063 

-€ 50,285 

Collecting and Sorting 

€ 6 

€ 12 

€ 6 

Total 

-€ 43,956 

-€ 142,498 

-€ 98,541 

Source: European Reference Model on Municipal Waste Management. 

27.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 27-1 and Table 27-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 11.5 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 27-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

28/05/2015 

349 

-€150-€100-€50€0€50€100€150€20020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 27-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

-€ 44 

-€ 142 

-€ 99 

-€ 0.5 

-€ 0.8 

-€ 0.34 

Financial Costs (social metric) 

€ 1,256 

€ 1,352 

€ 96 

€ 14.7 

€ 15.5 

€ 0.72 

Net Costs and Benefits 

€ 1,212 

€ 1,209 

-€ 2 

€ 14.3 

€ 14.7 

€ 0.38 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Poland depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 12.9 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

 
  
 
 
28.0  Portugal 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.341 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
28-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.342 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.343 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.5 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

341 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
342 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
343 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

351 

 
                                                   
 
value terms, with around half of the benefit coming from reduced environmental 
externalities and half from reduced financial costs.  

Table 28-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)344 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.29 

€ 0.18 

-€ 0.10 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

28.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Portugal with meetings 
held with the Portuguese Environment Agency (APA) and the Water and Waste Services 
Regulation Authority (ERSAR).345 In addition, further information was gathered via a detailed 

344 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
345 CRI (2013, June 7th) Notes from meeting in Portugal with APA and ERSAR, including additional feedback 
received after the visit.   

 
 
                                                   
 
questionnaire which was specifically developed to gather the required input data for the 
model.  

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

28.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 28-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.346  

The MSW generation projections are based on the Portuguese Environment Agency’s PERSU 
II projections. These extend until 2016, after which point an annual increase of 1% was 
assumed. The details of these projections are discussed in the technical documentation 
which accompanies the Municipal Waste Model.347 Interested readers should refer to this 
documentation for further details.  

Table 28-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

5,363 

4,987 

5,256 

5,524 

5,806 

Full Implementation Scenario (a) 

5,363 

4,987 

5,541 

5,810 

6,092 

70% Recycling Target Scenario (b) 

5,363 

4,987 

5,541 

5,849 

6,111 

Difference (b – a) 

0 

0 

0 

39 

19 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 

346 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
347 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

353 

 
                                                   
 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Portugal, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.348 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.349 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Portugal’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

28.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

348 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
349 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
The key figures for the two scenarios in 2030 are given in Table 7-3. It is important to note 
that Portugal has chosen to meet the 50% recycling target by means of calculation method 
2. Given the nature of this calculation method the country will be able to achieve the target 
by recycling 30% of the total municipal waste stream (see Full Implementation scenario in 
the table below which assumes full compliance with the Waste Framework Directive target 
by the county’s chosen calculation method). The 30% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.350 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.351 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 28-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

32% 

2.6% 

0.6% 

30% 

2.0% 

94% 

76% 

5.7% 

0.2% 

70% 

5.5% 

93% 

43% 

3.1% 

-0.4% 

40% 

3.4% 

-1.0% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Portugal has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, which 
is met, but can be achieved by only recycling 30% of all municipal waste. 

350 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
351 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

355 

 
 
                                                   
 
Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 2.2% 
and 5.6% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.352 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Portugal is 39% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

28.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 28-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Portugal the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 52%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 76% (Table 28-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 28-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

26% 

23% 

49% 

51% 

352 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
  
                                                   
 
The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 28-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 28-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

1,583 

1,418 

1,120 

4,121 

69% 

575 

515 

407 

1,496 

29% 

-1,008 

-903 

-713 

-2,625 

-40% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

28.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.353  Table 28-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 28-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

250 

0 

-250 

353 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

357 

 
 
 
                                                   
 
Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

697 

496 

106 

0 

0 

15 

-697 

-496 

-91 

0 

764 

764 

Source: European Reference Model on Municipal Waste Management. 

28.3 

Financial Costs 

28.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 28-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 28-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

99.8 

86 

14 

Labour Costs 

Mean Net Annual Earnings 

13,910 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

14 

23 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Mean Gross Annual Earnings 

21,943 

€ 

Eurostat 

Collection Frequencies 

Food Waste Collection 

1.7  Days between 

Eunomia 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

1.4 

2.5 

3.8 

collections 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 28-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 126 

€ 202 

€ 15 

€ 9 

€ 353 

€ 259 

€ 111 

€ 53 

€ 27 

€ 450 

€ 132 

-€ 91 

€ 39 

€ 18 

€ 98 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

28.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 

28/05/2015 

359 

 
 
 
Management Model.354 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Portugal are shown in Table 28-9. 

Table 28-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 61.86 

€ 0.00 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

28.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 28-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 28-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

million € 

354 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 450 

€ 225 

€ 675 

€ 353 

€ 301 

€ 654 

Source: European Reference Model on Municipal Waste Management. 

28.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.355 A number of the key country 
specific assumptions which have been made are shown in Table 28-11. 

Table 28-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

100 

0 

0 

0 

0 

400 

Kg CO2 eq / MWh 

Marginal Heat Mix 

31 

0 

18 

51 

% 

% 

% 

% 

€ 98 

-€ 77 

€ 21 

% 

% 

% 

% 

% 

355 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

361 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

0 

107 

26 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.356 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 28-12. Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 28-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

-€ 7,728 

-€ 17,248 

-€ 9,520 

-€ 33,864 

-€ 62,082 

-€ 28,218 

€ 3,388 

€ 8,646 

€ 5,258 

€ 3,311 

€ 8,262 

€ 4,951 

€ 804 

€ 107 

€ 3,948 

€ 3,144 

€ 522 

€ 416 

356 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 618 

€ 102 

€ 2,795 

€ 2,177 

€ 517 

€ 415 

Electricity Only 

€ 26,436 

€ 11,865 

-€ 14,572 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 12,997 

€ 4,115 

-€ 8,882 

Biodrying with no Plastics Recycling 

€ 0 

€ 0 

€ 0 

Biodrying with Plastics Recycling 

€ 1,601 

€ 586 

-€ 1,015 

AD based MBT 

€ 0 

€ 0 

€ 0 

Residual MRF + Combustion 

€ 10,409 

€ 3,666 

-€ 6,743 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

€ 49,634 

€ 24,160 

-€ 25,474 

Collection and Sorting 

€ 1 

€ 2 

€ 1 

Total 

€ 67,817 

-€ 10,245 

-€ 78,062 

Source: European Reference Model on Municipal Waste Management. 

28.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 28-1 and Table 7-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

28/05/2015 

363 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 8.1 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 28-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

-€100-€80-€60-€40-€20€0€20€40€6020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 28-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 68 

-€ 10 

-€ 78 

Financial Costs (social metric) 

€ 654 

€ 675 

€ 21 

Net Costs and Benefits 

€ 722 

€ 664 

-€ 57 

Source: European Reference Model on Municipal Waste Management. 

€ 0.7 

€ 6.6 

€ 7.4 

€ 0.4 

-€ 0.29 

€ 6.8 

€ 0.18 

€ 7.3 

-€ 0.10 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Portugal depends 
on the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 4.0 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

28/05/2015 

365 

 
 
 
29.0  Romania 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.357 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
29-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.358 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.359 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.7 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

357 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
358 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
359 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with around two thirds of the benefit coming from reduced environmental 
externalities and one third from reduced financial costs.  

Table 29-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)360 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.53 

€ 0.77 

€ 0.25 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

29.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Romania with meetings 
held with the Ministry of Environment and Climate Change (MOECC) and National 
Environmental Protection Agency (NEPA). In addition, further information was gathered via 

360 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

28/05/2015 

367 

 
 
                                                   
 
a detailed questionnaire which was specifically developed to gather the required input data 
for the model.361 

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

29.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 29-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.362  

MSW generation projections were based on the European Topic Centre projection using the 
methodology as reported in Andersen et al. (2007).363 Future waste arisings are assumed to 
return to pre-recession levels by 2025 and then remain stable as was indicated by the 
ETC/SCP projection (reflecting economic growth but decreasing population). The details of 
these projections are discussed in the technical documentation which accompanies the 
Municipal Waste Model.364 Interested readers should refer to this documentation for 
further details. 

The details of these projections are discussed in the technical documentation which 
accompanies the Municipal Waste Model.365 Interested readers should refer to this 
documentation for further details.  

361 Ministry of Environment and Climate Change and National Environmental Protection Agency (2013) 
Questionnare Information Returned Following Meetings With Eunomia on 27th & 28th May 2013 in Romania, 
27 May 2013 
362 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
363 Andersen, F. M., Larsen, H., Skovgaard, M., Moll, S. and Isoard, S. (2007) A European Model for Waste and 
Material ﬂows, Resources, Conservation and Recycling, Vol.49, pp. 421–435 
364 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 
365 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
Table 29-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

7,258 

8,000 

8,500 

9,000 

9,000 

Full Implementation Scenario (a) 

7,258 

8,000 

8,767 

9,263 

9,258 

70% Recycling Target Scenario (b) 

7,258 

8,000 

8,767 

9,405 

9,375 

Difference (b – a) 

0 

0 

0 

142 

117 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Romania, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.366 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.367 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 

366 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
367 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

369 

 
                                                   
 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Romania’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

29.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 29-3. It is important to note 
that Romania has chosen to meet the 50% recycling target by means of calculation method 
2. Given the nature of this calculation method the country will be able to achieve the target 
by recycling 27% of the total municipal waste stream (see Full Implementation scenario in 
the table below which assumes full compliance with the Waste Framework Directive target 
by the county’s chosen calculation method). The 27% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.368 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.369 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

368 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
369 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
                                                   
 
Table 29-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

29% 

2.5% 

0.8% 

27% 

1.7% 

94% 

74% 

5.3% 

0.3% 

69% 

5.0% 

93% 

45% 

2.8% 

-0.5% 

42% 

3.3% 

-0.9% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Romania has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, 
which is met, but can be achieved by only recycling 27% of all municipal waste. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 2.0% 
and 5.6% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.370 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Romania is 41% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

29.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 

370 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

371 

 
 
 
                                                   
 
Table 29-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Romania the figures show that if inputs to residual waste treatment plants 
were maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 53%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 76% (Table 7-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 29-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

49% 

0% 

49% 

51% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 29-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 29-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

4,492 

1,643 

-2,850 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

0 

2,087 

6,579 

73% 

0 

763 

2,406 

31% 

0 

-1,324 

-4,173 

-42% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

 
  
 
29.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.371  Table 29-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 29-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

471 

2,548 

1,609 

0 

0 

0 

0 

0 

-471 

-2,548 

-1,609 

69 

69 

2,766 

2,766 

Source: European Reference Model on Municipal Waste Management. 

29.3 

Financial Costs 

29.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 29-7 shows some of the key waste collection assumptions 
used in the modelling.  

371 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

373 

 
 
                                                   
 
Table 29-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

127.6 

52 

48 

Labour Costs 

Mean Net Annual Earnings 

4,293 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

26 

23 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

8,422 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

2.5 

2.5 

4.0 

6.5 

Average days 
between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

 
 
 
 
Table 29-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 114 

€ 218 

€ 30 

€ 17 

€ 379 

€ 309 

€ 174 

€ 95 

€ 49 

€ 627 

€ 195 

-€ 44 

€ 65 

€ 32 

€ 248 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

29.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.372 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Romania are shown in Table 29-9. 

372 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

375 

 
 
                                                   
 
Table 29-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 53.46 

€ 26.28 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

29.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 29-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 29-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 627 

€ 304 

€ 931 

€ 379 

€ 427 

€ 806 

€ 248 

-€ 123 

€ 125 

Source: European Reference Model on Municipal Waste Management. 

29.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.373 A number of the key country 
specific assumptions which have been made are shown in Table 29-11. 

373 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                   
 
Table 29-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

12 

34 

19 

1 

33 

% 

% 

% 

% 

% 

327 

Kg CO2 eq / MWh 

Marginal Heat Mix 

64 

25 

9 

2 

0 

% 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

226 

Kg CO2 eq / MWh 

25 

14 

42 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 

. The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As 
noted above, further detail and explanations about these externalities can be found in 

28/05/2015 

377 

 
Appendix 6 of the technical documentation which accompanies the Municipal Waste 
Model.374 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 29-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 29-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

-€ 8,723 

-€ 29,725 

-€ 21,002 

-€ 49,805 

-€ 90,307 

-€ 40,502 

€ 6,388 

€ 20,883 

€ 14,495 

€ 5,573 

€ 17,010 

€ 11,438 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 70,461 

€ 23,199 

-€ 47,262 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Landfill 

€ 111,377 

€ 57,969 

-€ 53,409 

374 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 3 

€ 5 

€ 2 

Total 

€ 135,273 

-€ 965 

-€ 136,239 

Source: European Reference Model on Municipal Waste Management. 

29.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 29-1 and Table 29-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 13.1 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

28/05/2015 

379 

 
Figure 29-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 29-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 135 

-€ 1 

-€ 136 

Financial Costs (social metric) 

€ 806 

€ 931 

€ 125 

€ 1.6 

€ 8.5 

€ 1.1 

-€ 0.53 

€ 9.2 

€ 0.77 

Net Costs and Benefits 

€ 942 

€ 930 

-€ 11 

€ 10.1 

€ 10.3 

€ 0.25 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Romania depends 
on the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 

-€150-€100-€50€0€50€100€150€20020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
the 70% recycling scenario is 2.6 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

28/05/2015 

381 

 
 
 
30.0  Slovakia 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.375 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
30-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.376 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.377 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.3 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

375 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
376 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
377 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with around half of the benefit coming from reduced environmental 
externalities and half from reduced financial costs.  

Table 30-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)378 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.15 

€ 0.05 

-€ 0.10 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

30.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Slovakia with a meeting 
held with the Centre of Waste Management and Environmental Management: Slovak 
Environmental Agency. In addition, further information was gathered via a detailed 
questionnaire which was specifically developed to gather the required input data for the 
model. Additional data and clarifications were obtained from Elena Bodíková, Director 
Centre of Waste Management and Environmental Management. 

378 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

28/05/2015 

383 

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

30.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 30-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.379  

The MSW generation projections used assume 500kg of MSW generation per inhabitant in 
2035. This figure was multiplied by projected population in 2035, and linearly interpolated 
back to latest year data (2011). The details of these projections are discussed in the 
technical documentation which accompanies the Municipal Waste Model.380 Interested 
readers should refer to this documentation for further details. 

Table 30-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

1,719 

1,930 

2,141 

2,353 

2,564 

Full Implementation Scenario (a) 

1,719 

1,930 

2,165 

2,377 

2,588 

70% Recycling Target Scenario (b) 

1,719 

1,930 

2,165 

2,388 

2,593 

Difference (b – a) 

0 

0 

0 

11 

5 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 

379 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
380 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
 
                                                   
 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Slovakia, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.381 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.382 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Slovakia’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

30.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

381 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
382 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

385 

 
                                                   
 
The key figures for the two scenarios in 2030 are given in Table 30-3. It is important to note 
that Slovakia has chosen to meet the 50% recycling target by means of calculation method 
2. Given the nature of this calculation method the country will be able to achieve the target 
by recycling 29% of the total municipal waste stream (see Full Implementation scenario in 
the table below which assumes full compliance with the Waste Framework Directive target 
by the county’s chosen calculation method). The 29% overall recycling rate is based on the 
waste composition data and the projected municipal waste arisings that are saved in the 
Municipal Waste Model.383 

This apparent discrepancy is due to the nature of the four calculation methods that Member 
States can select for measuring performance against the 50% recycling/preparation for 
reuse target.384 Of the four calculation methods only method 4 calculates the recycling rate 
based on the total amount of household and similar waste that is recycled. The other 
calculation methods allow Member States to achieve the target based on the recycling 
performance of individual waste streams. Thus, it is possible to achieve ‘50% 
recycling/preparation for reuse’ when substantially less than 50% of the total municipal 
waste stream is being recycled/prepared for reuse. 

Table 30-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

31% 

2.9% 

0.6% 

29% 

2.2% 

93% 

74% 

6.0% 

0.2% 

68% 

5.8% 

92% 

43% 

3.2% 

-0.4% 

39% 

3.6% 

-0.8% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

2. Slovakia has chosen Method 2 to calculate the country’s performance against the WFD target of 50%, which 
is met, but can be achieved by only recycling 29% of all municipal waste. 

383 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
384 For more details on the different calculation methods see Appendix 7 of the following report: Eunomia 
Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste 
Generation and Management, Report for European Commission Directorate-General for the Environment, 
February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
                                                   
 
Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 2.9% 
and 6.6% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.385 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Slovakia is 39% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

30.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 30-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Slovakia the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 49%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 77% (Table 30-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 30-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Source: European Reference Model on Municipal Waste Management. 

Full Implementation 

24% 

28% 

52% 

48% 

385 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

387 

 
  
                                                   
 
The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 30-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

624 

720 

430 

1,774 

70% 

237 

273 

163 

672 

31% 

-388 

-447 

-267 

-1,102 

-39% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste. 

30.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.386  Table 30-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 30-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

125 

0 

-125 

386 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
 
                                                   
 
Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

Full 
Implementation 

70% Recycling 
Target 

Difference 

456 

510 

80 

0 

0 

0 

36 

-456 

-510 

-44 

797 

797 

Source: European Reference Model on Municipal Waste Management. 

30.3 

Financial Costs 

30.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 30-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 30-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

105.0 

45 

55 

Labour Costs 

Mean Net Annual Earnings 

9,775 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

13 

26 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Mean Gross Annual Earnings 

16,028 

€ 

Eurostat 

Collection Frequencies 

Food Waste Collection 

5.0  Days between 

Eunomia 

28/05/2015 

389 

 
 
Assumption 

Value 

Unit 

Source 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

6.3 

7.5 

collections 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

Table 30-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 22 

€ 55 

€ 5 

€ 2 

€ 84 

€ 59 

€ 40 

€ 25 

€ 11 

€ 135 

€ 37 

-€ 15 

€ 20 

€ 9 

€ 51 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

30.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 

 
 
 
Management Model.387 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Slovakia are shown in Table 30-9. 

Table 30-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 75.39 

€ 37.07 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

30.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 30-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 30-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

million € 

387 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

391 

 
                                                   
 
Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 135 

€ 76 

€ 211 

€ 84 

€ 124 

€ 208 

Source: European Reference Model on Municipal Waste Management. 

30.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.388 A number of the key country 
specific assumptions which have been made are shown in Table 30-11. 

Table 30-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

8 

16 

53 

3 

20 

179 

Kg CO2 eq / MWh 

Marginal Heat Mix 

52 

23 

12 

6 

% 

% 

% 

% 

€ 51 

-€ 48 

€ 3 

% 

% 

% 

% 

% 

388 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
                                                   
 
Assumption 

Value 

Unit 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

Incinerator Generation Efficiencies 

7 

214 

25 

14 

42 

80 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.389 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 30-12. Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 30-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
s
e
g
i
D

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

-€ 1,195 

-€ 7,404 

-€ 6,209 

-€ 19,702 

-€ 34,450 

-€ 14,748 

€ 1,604 

€ 5,789 

€ 4,185 

€ 952 

€ 2,984 

€ 2,032 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

389 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

393 

 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Electricity Only 

€ 17,533 

€ 7,153 

-€ 10,380 

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

AD based MBT 

€ 6,763 

€ 2,238 

-€ 4,525 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

Landfill 

€ 23,092 

€ 13,024 

-€ 10,068 

Collection and Sorting 

€ 1 

€ 2 

€ 1 

Total 

€ 29,048 

-€ 10,664 

-€ 39,712 

Source: European Reference Model on Municipal Waste Management. 

30.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 30-1and Table 30-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 

 
 
 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 3.2 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

Figure 30-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

28/05/2015 

395 

-€50-€40-€30-€20-€10€0€10€2020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
Table 30-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 29 

-€ 11 

-€ 40 

Financial Costs (social metric) 

€ 208 

€ 211 

€ 3 

Net Costs and Benefits 

€ 237 

€ 200 

-€ 37 

Source: European Reference Model on Municipal Waste Management. 

€ 0.3 

€ 2.1 

€ 2.4 

€ 0.2 

-€ 0.15 

€ 2.1 

€ 0.05 

€ 2.3 

-€ 0.10 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Slovakia depends 
on the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 1.0 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

 
  
 
 
31.0  Slovenia 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.390 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 7-1 
shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.391 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.392 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.06 billion (in 2014 real term prices) over the period from 2014-2030 in net 

390 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
391 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
392 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

397 

 
                                                   
 
present value terms, with around two thirds of the benefit coming from reduced 
environmental externalities and one third from reduced financial costs.  

Table 31-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)393 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.04 

€ 0.01 

-€ 0.03 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

31.1  Waste Generation and Management Projections 

Information was provided by the Waste Department of the Slovenian Ministry of Agriculture 
and Environment and the Slovenian Environment Agency, via return of a detailed 
questionnaire which was specifically developed to gather the required input data for the 
model. 

393 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

31.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 31-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.394  

The MSW generation projections are based on modelling conducted by Slovenia’s 
Operational Programme on Municipal Waste Management. These extend until 2020, after 
which point an annual increase of 0.7% was assumed, equal to the estimated rate of growth 
between 2018 and 2020. Further details of these projections are discussed in the technical 
documentation which accompanies the Municipal Waste Model.395 Interested readers 
should refer to this documentation for further details. 

Table 31-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

844 

865 

889 

921 

953 

Full Implementation Scenario (a) 

70% Recycling Target Scenario (b) 

Difference (b – a) 

844 

844 

0 

865 

865 

0 

886 

886 

0 

918 

912 

-6 

950 

939 

-11 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 

394 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
395 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

399 

 
                                                   
 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Slovenia, the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the two scenarios. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.396 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Slovenia’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

31.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 7-3. Slovenia has chosen to 
calculate the Waste Framework Directive recycling target of 50% by means of calculation 
method 4. This is equivalent to the Total MSW Recycling Rate figure below (50%). 

396 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
 
                                                   
 
Table 31-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

53% 

4.2% 

0.8% 

50% 

3.4% 

94% 

76% 

5.9% 

0.4% 

70% 

5.5% 

93% 

22% 

1.8% 

-0.3% 

20% 

2.1% 

-0.9% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 3.3% 
and 5.6% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.397 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Slovenia is 20% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

31.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 31-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 

397 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

401 

 
 
                                                   
 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Slovenia the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 77%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 76% (Table 31-3), waste will not have to be diverted 
from the planned MBT and incineration plants. 

Table 31-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

22% 

1% 

23% 

77% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 31-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 31-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

206 

12 

225 

443 

50% 

107 

6 

116 

229 

30% 

-99 

-6 

-109 

-214 

-20% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

 
  
 
31.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.398  Table 31-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 31-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

15 

136 

40 

0 

0 

0 

6 

0 

0 

-15 

-130 

185 

145 

Source: European Reference Model on Municipal Waste Management. 

31.3 

Financial Costs 

31.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 31-7 shows some of the key waste collection assumptions 
used in the modelling.  

398 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

403 

 
 
 
 
 
                                                   
 
Table 31-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Kerbside sort 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

138.0 

69 

31 

Labour Costs 

Mean Net Annual Earnings 

16,927 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

23 

15 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

27,214 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Average days 
between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

 
 
 
 
Table 31-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 48 

€ 31 

€ 3 

€ 2 

€ 84 

€ 55 

€ 27 

€ 6 

€ 4 

€ 93 

€ 7 

-€ 4 

€ 3 

€ 2 

€ 9 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

31.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.399 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Slovenia are shown in Table 31-9. 

399 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

405 

 
 
                                                   
 
Table 31-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 53.58 

€ 38.62 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

31.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 31-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 31-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 93 

€ 22 

€ 114 

€ 84 

€ 29 

€ 113 

€ 9 

-€ 7 

€ 1 

Source: European Reference Model on Municipal Waste Management. 

31.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.400 A number of the key country 
specific assumptions which have been made are shown in Table 31-11. 

400 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                   
 
Table 31-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

0 

100 

0 

0 

0 

% 

% 

% 

% 

% 

800 

Kg CO2 eq / MWh 

Marginal Heat Mix 

68 

11 

0 

10 

11 

% 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

186 

Kg CO2 eq / MWh 

25 

14.8 

44.4 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

28/05/2015 

407 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.401 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 31-12. Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 31-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

Electricity Only 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

-€ 692 

-€ 3,215 

-€ 2,522 

-€ 12,340 

-€ 16,033 

-€ 3,693 

€ 909 

€ 608 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 1,567 

€ 1,009 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 658 

€ 401 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

-€ 367 

-€ 251 

€ 115 

€ 0 

€ 24 

€ 0 

€ 15 

€ 0 

-€ 9 

€ 3,979 

€ 1,878 

-€ 2,101 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Landfill 

€ 13,730 

€ 8,651 

-€ 5,079 

401 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 1 

€ 1 

€ 0 

Total 

€ 5,852 

-€ 6,378 

-€ 12,230 

Source: European Reference Model on Municipal Waste Management. 

31.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 31-1Figure 31-1 and Table 31-13. From 
this it is clear that there is a net benefit to be gained from moving towards higher recycling 
rates (this is shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 0.7 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

28/05/2015 

409 

 
Figure 31-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 31-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 6 

-€ 6 

-€ 12 

Financial Costs (social metric) 

€ 113 

€ 114 

€ 1 

€ 0.1 

€ 1.3 

€ 0.0 

-€ 0.04 

€ 1.3 

€ 0.01 

Net Costs and Benefits 

€ 119 

€ 108 

-€ 11 

€ 1.3 

€ 1.3 

-€ 0.03 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Slovenia depends 
on the amount of waste that is processed within the country’s borders as opposed to being 

-€14-€12-€10-€8-€6-€4-€2€0€2€420112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 
the 70% recycling scenario is 0.3 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

28/05/2015 

411 

 
  
 
 
32.0  Spain 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.402 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
32-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.403 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.404 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.9 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

402 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
403 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
404 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with just over half of the benefit coming from reduced environmental 
externalities and just under half from reduced financial costs.  

Table 32-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)405 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.40 

-€ 0.40 

-€ 0.80 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

32.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Spain with meetings 
held in the Ministry of Agriculture, Food and Environment with participants from the 
Ministry, the Spanish Statistical Office – Section for Environmental Statistics, and the Urban 
Ecology Agency of Barcelona (BCNecologia).406 In addition, further information was gathered 

405 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
406 CRI (2013, June 22th) Notes from meeting in Spain with Ministry of Agriculture, Food and Environment, 
Spanish Statistical Office and BCNecologia, including additional feedback received after the visit.   

28/05/2015 

413 

 
 
                                                   
 
via a detailed questionnaire which was specifically developed to gather the required input 
data for the model.  

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

32.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 32-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.407  

Waste generation has been in decline since 2008 in Spain, mostly due to the economic crisis. 
Equally, the GDP of Spain, as well as the private consumption expenditure has still not 
recovered. The MSW generation projections used assume a 0.3% annual increase in MSW 
generation, on the basis that the economic recovery is unlikely to increase significantly in 
the near future. This significantly moderates previous arising projections made for Spain, 
such as those used in the previous EEA model.408 The details of these projections are 
discussed further in the technical documentation which accompanies the Municipal Waste 
Model.409 Interested readers should refer to this documentation for further details.  

Table 32-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

23,674 

23,274 

23,625 

23,982 

24,344 

Full Implementation Scenario (a) 

23,674 

23,274 

24,371 

24,744 

25,121 

70% Recycling Target Scenario (b) 

23,674 

23,274 

24,371 

24,656 

24,995 

Difference (b – a) 

0 

0 

0 

-89 

-126 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 

407 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
408 ETC/SCP (2011) Projections of Municipal Waste Management and Greenhouse Gases, Prepared by Bakas et 
al., 89 pp. Copenhagen, Denmark http://scp.eionet.europa.eu/publications/2011WP4 
409 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Spain, the waste prevention impacts of PAYT and separate food waste collections 
are lower than the volume of additional garden waste collected, resulting in a net increase 
in waste arisings under the two scenarios. Further details on garden waste collections can 
be found in Section 4.5.3 of Appendix 5 which accompanies the European Municipal Waste 
Model.410 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.411 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Spain’s presented in Table 2 of the accompanying Member 
State Data Table.     

32.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

410 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
411 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

415 

 
                                                   
 
1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 7-3. Spain has chosen to 
calculate the Waste Framework Directive recycling target of 50% by means of calculation 
method 4. This is equivalent to the Total MSW Recycling Rate figure below (50%). 

Table 32-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

55% 

5.5% 

0.5% 

50% 

5.0% 

91% 

73% 

7.2% 

0.3% 

66% 

6.8% 

91% 

18% 

1.7% 

-0.2% 

16% 

1.9% 

-0.3% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 5.5% 
and 7.9% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.412 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Spain is 20% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 

412 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
                                                   
 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

32.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 32-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Spain the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 69%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 32-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 32-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

27% 

4% 

31% 

69% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 32-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 32-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

6,787 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

925 

3,548 

11,260 

4,023 

549 

2,103 

6,674 

28/05/2015 

-2,764 

-377 

-1,445 

-4,585 

417 

 
  
 
Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Total, % of MSW 

49% 

33% 

-16% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

32.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.413  Table 32-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 32-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

42 

0 

0 

0 

0 

0 

-42 

5,849 

162 

-5,687 

2,917 

8,646 

5,728 

Source: European Reference Model on Municipal Waste Management. 

413 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
 
                                                   
 
32.3 

Financial Costs 

32.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 32-7 shows some of the key waste collection assumptions 
used in the modelling.  

Table 32-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

102.4 

71 

29 

Labour Costs 

Mean Net Annual Earnings 

24,785 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

9 

27 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

38,728 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

1.7 

1.4 

2.5 

3.8 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 
2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

28/05/2015 

419 

 
 
 
Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion). 

Table 32-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

€ 1,057 

€ 1,189 

Collection of Residual Waste 

CA Sites 

Communications Cost 

€ 614 

€ 170 

€ 60 

€ 415 

€ 250 

€ 95 

Total Cost 

€ 1,901 

€ 1,949 

Source: European Reference Model on Municipal Waste Management. 

€ 132 

-€ 199 

€ 80 

€ 34 

€ 47 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

32.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.414 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

414 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
   
 
 
                                                   
 
When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Spain are shown in Table 32-9. 

Table 32-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 69.85 

€ 0.00 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

32.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 32-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 32-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

€ 1,901 

€ 996 

€ 2,898 

million € 

€ 1,949 

€ 831 

€ 2,779 

€ 47 

-€ 166 

-€ 118 

Source: European Reference Model on Municipal Waste Management. 

32.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.415 A number of the key country 
specific assumptions which have been made are shown in Table 32-11. 

415 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 

28/05/2015 

421 

 
                                                   
 
Table 32-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

32 

9 

21 

8 

31 

% 

% 

% 

% 

% 

242 

Kg CO2 eq / MWh 

Marginal Heat Mix 

28 

11 

51 

10 

0 

% 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

217 

Kg CO2 eq / MWh 

25 

14 

42 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                                                                                                                              
 
The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.416 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 32-12.  Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 32-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

-€ 30,128 

-€ 41,784 

-€ 11,657 

Recycling 

-€ 197,322 

-€ 235,379 

-€ 38,057 

Open Air Composting 

€ 12,031 

€ 15,448 

€ 3,417 

In-Vessel Composting 

€ 11,067 

€ 14,112 

€ 3,046 

AD - Electricity Only 

€ 14,258 

€ 20,297 

€ 6,039 

AD - CHP 

AD - Gas to Grid 

€ 1,894 

€ 2,696 

€ 802 

€ 9,453 

€ 13,376 

€ 3,923 

AD - Gas to Vehicle Fuel 

€ 1,716 

€ 2,449 

€ 733 

Electricity Only 

€ 26,073 

€ 20,889 

-€ 5,184 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 67,947 

€ 39,187 

-€ 28,760 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

AD based MBT 

€ 21,900 

€ 12,738 

-€ 9,162 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

416 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

423 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

Landfill 

€ 203,048 

€ 155,256 

-€ 47,791 

Collection and Sorting 

€ 11 

€ 14 

€ 3 

Total 

€ 141,948 

€ 19,300 

-€ 122,648 

Source: European Reference Model on Municipal Waste Management. 

32.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 32-1 and Table 32-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 10.4 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

 
Figure 32-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 32-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 142 

€ 19 

-€ 123 

€ 1.8 

€ 1.4 

-€ 0.40 

Financial Costs (social metric) 

€ 2,898 

€ 2,779 

-€ 118 

€ 31.0 

€ 30.6 

-€ 0.40 

Net Costs and Benefits 

€ 3,040 

€ 2,799 

-€ 241 

€ 32.8 

€ 32.0 

-€ 0.80 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Spain depends on 
the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 

28/05/2015 

425 

-€250-€200-€150-€100-€50€020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
the 70% recycling scenario is 6.3 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

 
  
 
 
 
33.0  Sweden 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.417 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
33-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.418 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.419 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €0.2 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

417 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
418 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
419 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

28/05/2015 

427 

 
                                                   
 
value terms, with just under half of the benefit coming from reduced environmental 
externalities and just over half from reduced financial costs.  

Table 33-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)420 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 0.07 

-€ 0.07 

-€ 0.14 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

33.1  Waste Generation and Management Projections 

As part of the model development process a visit was conducted to Sweden with meetings 
held with the Swedish Environmental Protection Agency and the Swedish Environmental 
Institute (IVL). 421 In addition, further information was gathered via a detailed questionnaire 
which was specifically developed to gather the required input data for the model. 

420 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 
421 CRI (2013, June 26th) Notes from meeting in Sweden with Swedish Environmental Protection Agency and 
the IVL, including additional feedback received after the visit.   

 
 
                                                   
 
The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

33.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 33-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.422  

MSW generation projections were developed by members of the project team, using the 
methodology described in Andersen et al. (2007).423 The details of these projections are 
discussed in the technical documentation which accompanies the Municipal Waste 
Model.424 Interested readers should refer to this documentation for further details. 

Table 33-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

4,350 

4,792 

5,113 

5,377 

5,673 

Full Implementation Scenario (a) 

4,350 

4,792 

5,113 

5,377 

5,673 

70% Recycling Target Scenario (b) 

4,350 

4,792 

5,113 

5,363 

5,634 

Difference (b – a) 

0 

0 

0 

-14 

-39 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 

422 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
423 Andersen, F., M., Larsen, H., Skovgaard, M. Moll, S. and Isoard, S. (2007). A European Model for Waste and 
Material Flows. Resources, Conservation and Recycling 49 (4): 421–435. 
424 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

429 

 
                                                   
 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of Sweden, the waste prevention impacts of PAYT result in a net reduction in waste 
arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.425 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for Sweden’s MSW stream is presented in Table 2 of the 
accompanying Member State Data Table.   

33.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 33-3. It is interesting to note 
that Sweden has chosen to calculate the Waste Framework Directive recycling target of 50% 
by means of calculation method 2, which the model estimates at 68%. However, the model 
suggests that the total MSW recycling rate in 2020 (e.g. method 4) would be higher than the 
target (56%), suggesting Sweden would meet the target even if method 4 had been 
selected.  

425 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
Table 33-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

63% 

6.6% 

0.0% 

56% 

6.6% 

90% 

77% 

7.8% 

0.0% 

69% 

7.8% 

90% 

14% 

1.2% 

0.0% 

13% 

1.2% 

0.3% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 6.7% 
and 8.2% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.426 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for Sweden is 14% (i.e. the 
amount of additional recycling that will have to be collected in 2030 to move from Full 
Implementation to achieving the 70% recycling target which is calculated after material 
losses have been taken into account). This increase in recycling results in direct costs and 
benefits to capture and treat the material, but the captured material means that less 
residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

33.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 33-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 

426 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

431 

 
 
                                                   
 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For Sweden the figures show that if inputs to residual waste treatment plants were 
maintained as under the Full Implementation scenario, the total waste collected for 
recycling would be limited to 60%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 33-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 33-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

0% 

36% 

36% 

64% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 33-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 33-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

0 

0 

Direct Inputs to Incineration Plants 

2,042 

1,248 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

57 

2,098 

41% 

35 

1,283 

28% 

0 

-794 

-22 

-816 

-13% 

Source: European Reference Model on Municipal Waste Management. 

Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

 
  
 
33.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.427  Table 33-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 33-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

8 

630 

716 

0 

0 

0 

8 

0 

0 

-8 

-621 

1,344 

629 

Source: European Reference Model on Municipal Waste Management. 

33.3 

Financial Costs 

33.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 33-7 shows some of the key waste collection assumptions 
used in the modelling.  

427 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

28/05/2015 

433 

 
 
                                                   
 
Table 33-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

107.9 

92 

8 

Labour Costs 

Mean Net Annual Earnings 

37,547 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

20 

32 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

78,499 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

 
 
 
 
Table 33-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Million € 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

€ 327 

€ 178 

€ 49 

€ 8 

€ 563 

€ 340 

€ 160 

€ 66 

€ 16 

€ 583 

€ 13 

-€ 18 

€ 17 

€ 8 

€ 20 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

33.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.428 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in Sweden are shown in Table 33-9. 

428 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

435 

 
 
                                                   
 
Table 33-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 47.33 

€ 57.99 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

33.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 33-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 33-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

million € 

€ 583 

€ 238 

€ 821 

€ 563 

€ 291 

€ 854 

€ 20 

-€ 53 

-€ 33 

Source: European Reference Model on Municipal Waste Management. 

33.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.429 A number of the key country 
specific assumptions which have been made are shown in Table 33-11. 

429 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
                                                   
 
Table 33-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

100 

0 

0 

0 

0 

% 

% 

% 

% 

% 

400 

Kg CO2 eq / MWh 

Marginal Heat Mix 

Incinerator Generation Efficiencies 

0 

0 

0 

100 

0 

1 

25 

12 

83 

93 

% 

% 

% 

% 

% 

Kg CO2 eq / MWh 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

28/05/2015 

437 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.430 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 33-12. Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 33-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

Open Air Composting 

In-Vessel Composting 

AD - Electricity Only 

AD - CHP 

AD - Gas to Grid 

€ 0 

-€ 3,984 

-€ 3,984 

-€ 63,030 

-€ 71,642 

-€ 8,612 

€ 3,441 

€ 3,959 

€ 3,895 

€ 4,698 

€ 0 

€ 216 

€ 2 

€ 0 

€ 299 

€ 3 

€ 518 

€ 803 

€ 0 

€ 82 

€ 1 

AD - Gas to Vehicle Fuel 

€ 3,231 

€ 4,460 

€ 1,230 

Electricity Only 

€ 53,338 

€ 37,149 

-€ 16,189 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

Biodrying with no Plastics Recycling 

Biodrying with Plastics Recycling 

AD based MBT 

Residual MRF + Combustion 

€ 0 

€ 0 

€ 0 

€ 4,455 

€ 3,120 

-€ 1,335 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

€ 3,774 

€ 2,531 

-€ 1,243 

430 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 3 

€ 3 

€ 0 

Total 

€ 9,324 

-€ 19,404 

-€ 28,729 

Source: European Reference Model on Municipal Waste Management. 

33.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 33-1 and Table 33-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 0.8 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

28/05/2015 

439 

 
Figure 33-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 33-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 9 

-€ 19 

-€ 29 

Financial Costs (social metric) 

€ 854 

€ 821 

-€ 33 

€ 0.1 

€ 8.9 

€ 0.0 

-€ 0.07 

€ 8.9 

-€ 0.07 

Net Costs and Benefits 

€ 863 

€ 801 

-€ 62 

€ 9.0 

€ 8.9 

-€ 0.14 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in Sweden depends 
on the amount of waste that is processed within the country’s borders as opposed to being 
exported for treatment abroad. The estimated increase in direct employment in 2030 under 

-€70-€60-€50-€40-€30-€20-€10€020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
the 70% recycling scenario is 0.7 thousand FTEs. Note that this is direct employment only 
with no provision for multiplier effects. 

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441 

 
  
 
 
 
34.0  United Kingdom 

This country report aims to provide an overview of the key country specific assumptions and 
presents some detailed model outputs. The intention is to help Member States understand 
the key parameters which underpin the analysis and how the model results are calculated.   
It is hoped that that this summary report will provide greater transparency and clarity in the 
results, and demonstrate what type of outputs can be generated by the Municipal Waste 
Model. 

The Impact Assessment included results from a range of scenarios in order to derive a 
‘preferred scenario’ and inform the legislative proposal. This report provides further 
information regarding the scenario which models a recycling target of 70% in 2030 for 
municipal waste. No other targets or waste streams are included at this stage.431 All results 
are shown relative to a scenario in which the existing targets in the Waste Framework and 
Landfill Directives are being met (this scenario is known as ‘Full Implementation’). Table 
34-1 shows the overall results which are generated by the Municipal Waste Model.    

For the sake of clarity it is worth summarising what is meant by each scenario: 

  Full Implementation Scenario – This scenario assumes full implementation of the 

existing targets. This includes the current 50% recycling/preparation for reuse target 
in the Waste Framework Directive, performance against which can be measured by 
one of four methods.432 In this scenario it was assumed that the 50% 
recycling/preparation for reuse target in 2020 will be achieved by means of the 
country’s chosen calculation method.433 This scenario also assumes full compliance 
with the Landfill Directive target for the diversion of biodegradable municipal waste 
from landfill.  

  70% Recycling Scenario – This scenario assumes that Member States will use their 

chosen method for the existing 2020 target. It then sets an interim 
recycling/preparation for reuse target of 60% in 2025, increasing to 70% in 2030. The 
2025 and 2030 targets in this scenario are calculated using Method 4 for all Member 
States (i.e. % total municipal solid waste recycled/prepared for reuse). 

For the 70% scenario mentioned above, the model suggests a net benefit to society of 
around €2.0 billion (in 2014 real term prices) over the period from 2014-2030 in net present 

431 See Option 3.1-high in European Commission (2014) Impact Assessment Accompanying the Document: 
Proposal for Reviewing the European Waste Management Targets, July 2014, 
http://ec.europa.eu/environment/waste/target_review.htm 
432 Commission Decision of 18 November 2011, Establishing Rules and Calculation Methods for Verifying 
Compliance with the Targets set in Article 11(2) of Directive 2008/98/EC of the European Parliament and of the 
Council, Decision 2011/753/EU, http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2011:310:0011:0016:EN:PDF 
433 See Section 8.1, Table 8-1 in Eunomia Research & Consulting, Copenhagen Resource Institute, and Öko-
Institut (2014) Impact Assessment on Options Reviewing Targets in the Waste Framework Directive, Landfill 
Directive and Packaging and Packaging Waste Directive, February 2014, 
http://ec.europa.eu/environment/waste/pdf/target_review/Targets%20Review%20final%20report.pdf 

 
                                                   
 
value terms, with around three quarters of the benefit coming from reduced environmental 
externalities and one quarter from reduced financial costs.  

Table 34-1: Overall Results from CBA - 70% Scenario Compared to Full 
Implementation, Net Present Value 2014 to 2030 (€bn, 2014 prices)434 

Environmental Externalities 

Financial Costs (social metric) 

Net Costs and Benefits 

Net Present Value  

billion € 2014 to 2030 

-€ 1.61 

-€ 0.06 

-€ 1.67 

Note: Negative costs denote savings/benefits to society, whilst positive costs denote an overall cost/disbenefit 
to society.   
Source: European Reference Model on Municipal Waste Management. 

The following sections outline the key model assumptions and intermediate results that 
help explain the model results. The following are considered: 

1.  The key differences between the waste generation and management projections for 

the Full Implementation and 70% Recycling Target scenarios; 

2.  The assumed change in collection systems between the two scenarios, including the 

influence of loss rates on overall performance; 

3.  The collection costs per household and the total collection costs for dry recycling, 

biowaste, and refuse; 

4.  The change in the amount of waste flowing into waste treatment facilities, the unit 

costs of operating the facilities and the total costs; 

5.  The drivers of the change in GHG emissions from the management of the waste;  
6.  The monetised environmental externalities; and 
7.  The overall stream of costs and benefits used to arrive at the NPV figures indicated 

above. 

The sections below systematically work through the points above in order to provide a 
methodical overview of how the CBA analysis was built up. 

34.1  Waste Generation and Management Projections 

The United Kingdom (UK) consists of four nations: England, Wales, Scotland and Northern 
Ireland. Each has different regulatory and enforcement bodies responsible for waste 
management within its jurisdiction. For the purposes of liaison with the European 
Commission, recognising that the 4 countries are not bona fide Member States in their own 
right, Defra has lead responsibility. Information was therefore provided by a contact at 

434 The Net Present Value, or NPV, is the current value of the total stream of costs and benefits in each year 
from 2014 to 2030, with future years discounted at the social discount rate of 4%. 

28/05/2015 

443 

 
 
                                                   
 
Defra in England, via return of a detailed questionnaire which was specifically developed to 
gather the required input data for the model. 

The model works by firstly taking projections of the total waste generation in the country, 
then considering the quantity of waste recycled and finally looking at how the remaining 
residual waste is managed. The sections below are organised in this way. 

34.1.1  Waste Generation 

The assumed waste generation projections used for calculating the results is presented in 
Table 34-2. For more details on the waste generation projections used in the model please 
refer to the discussion in Sections 5.1.1 and 5.1.2 of the main modelling report and the 
country specific reports presented in Appendix 1.435  

The MSW generation projections are based on projections conducted by the UK Department 
for Environment, Food & Rural Affairs. 436 The details of these projections are discussed in 
the technical documentation which accompanies the Municipal Waste Model.437 Interested 
readers should refer to this documentation for further details. 

Table 34-2: Projected Waste Arisings 

Year 

2011 

2015 

2020 

2025 

2030 

Thousand tonnes 

Total Generation – With no  Changes in 
Waste Collection System 

55,802 

51,723 

52,609 

52,419 

52,236 

Full Implementation Scenario (a) 

55,802 

51,723 

52,592 

52,418 

52,235 

70% Recycling Target Scenario (b) 

55,802 

51,723 

52,592 

52,166 

51,782 

Difference (b – a) 

0 

0 

0 

-252 

-453 

Source: total waste generation figures from Appendix 1 in: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The model calculates the change in the amount of collected waste due to the change in 
collection systems over time. For many Member States the generation figures under the 

435 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 
436 DEFRA (2013) Forecasting 2020 Waste Arisings and Treatment Capacity, October 2013, 
www.gov.uk/government/publications/forecasting-2020-waste-arisings-and-treatment-capacity 
437 See Appendix 1 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development 
of a Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-
General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

 
                                                   
 
two scenarios are higher than the initial projections (Total Generation – With no Change in 
Waste Collection System) due to increases in garden waste collection services which results 
in more garden material in the waste stream. These increases are counteracted by the 
waste prevention impact of introducing pay as you throw (PAYT) services (see Figure 4-1) 
and/or by the reduction in food waste arisings resulting from the introduction of separate 
food waste collections (an assumed requirement for achieving higher recycling rates). In the 
case of the United Kingdom, the waste prevention impacts of PAYT result in a net reduction 
in waste arisings under the 70% recycling scenario. 

The amount of waste generated by material is calculated using a waste composition for 
each Member State. As far as possible, data on the composition of the total municipal waste 
stream was gathered directly from Member States via the consultation process undertaken 
as part of the model development.438 It is widely acknowledged, however, that the quality of 
these data varies significantly and in many instances Member States have not yet 
undertaken detailed analysis of their municipal waste stream. The details of the 
compositional data which were gathered and used in the model are outlined for each 
Member State in Appendix 1 of modelling report signposted in the introduction. Where data 
were not available these limitations are discussed and alternative sources of information 
were suggested for inclusion in the model.  

The assumed composition for the United Kingdom’s MSW stream is presented in Table 2 of 
the accompanying Member State Data Table.   

34.1.2  Recycling Projections 

One of the key model inputs driving the overall results is the projected recycling rate. To 
understand how the recycling rate influences the results of the CBA we need to understand 
the change in the recycling rate between the Full Implementation and 70% Recycling Target 
scenarios. In addition, there are some co-determinants of the overall recycling rate. The 
three main elements are: 

1.  The total quantity of waste collected for recycling which is segregated from mixed 

waste; 

2.  The total quantity of waste lost between the point of collection and its being 

recycled; and 

3.  The total quantity of waste extracted for recycling at mixed waste treatment plants 

(such as mechanical biological treatment). 

The key figures for the two scenarios in 2030 are given in Table 34-3. It is important to note 
that the UK has chosen to meet the 50% recycling target by means of calculation method 3. 

438 See Section 2.0 of the main report accompanying the European Reference Model on Municipal Waste 
Management: Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a 
Modelling Tool on Waste Generation and Management, Report for European Commission Directorate-General 
for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-
management-model.zip 

28/05/2015 

445 

 
                                                   
 
The overall recycling rate is based on the waste composition data and the projected 
municipal waste arisings that are saved in the Municipal Waste Model. 439 

Table 34-3: Change in the Components of Overall Recycling Rate as a 
Proportion of Total Municipal Waste, 2030 

Waste Collected for Recycling (a) 

Collection and Recycling Loss Rate1 (b) 

Recycling Captured from Mixed Waste (c) 

Total MSW Recycling Rate (d = a - b + c) 

Difference between Recycling Collection Rate and 
the Total MSW Recycling Rate (a - d) 

Collection Efficiency (d / a) 

Note:  

Full 
Implementation 

70% Recycling 
Target 

Difference 

55% 

5.2% 

0.3% 

50% 

4.9% 

91% 

77% 

7.6% 

0.2% 

70% 

7.4% 

90% 

23% 

2.4% 

-0.2% 

20% 

2.5% 

-0.6% 

1. These loss rates are calculated as a proportion of total MSW so they may appear lower than expected. 
2. The United Kingdom has chosen Method 3 to calculate the country’s performance against the WFD target of 
50%. 

Source: European Reference Model on Municipal Waste Management. 

These figures show that, under the Full Implementation and 70% recycling scenarios, 5.2% 
and 8.0% respectively more waste needs to be collected than the overall recycling rate to 
meet the recycling target, despite the contribution of recycling from mixed waste 
treatment. Further details on the types of mixed waste treatment are given in Section 2.10 
of Appendix 2 of the Municipal Waste Model report.440 The key driver of the net costs and 
benefits figure is the difference in the total recycling rate, which for the United Kingdom is 
20% (i.e. the amount of additional recycling that will have to be collected in 2030 to move 
from Full Implementation to achieving the 70% recycling target which is calculated after 
material losses have been taken into account). This increase in recycling results in direct 
costs and benefits to capture and treat the material, but the captured material means that 
less residual waste (or refuse) is generated and therefore the amount of material going to 
residual waste treatment plants declines over time. This is further explained in the next 
section. 

439 See Appendix 1 of the following report for more details: Eunomia Research & Consulting, and Copenhagen 
Resource Institute (2014) Development of a Modelling Tool on Waste Generation and Management, Report for 
European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 
440 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
                                                   
 
34.1.3  Residual Waste Management 

In addition to the management of separately collected dry recycling and biowastes, the 
management of residual waste has a significant impact on the overall costs and benefits. 
Table 34-4 shows the proportion of MSW that is sent to MBT and incineration plants. The 
remainder is either recycled or landfilled. The presence of treatment plants in a country 
(which will most likely require set minimum input tonnages in the contracts with 
municipalities) can limit the total amount of recycling that could theoretically take place in a 
country. For the United Kingdom the figures show that if inputs to residual waste treatment 
plants were maintained as under the Full Implementation scenario, the total waste collected 
for recycling would be limited to 67%. Therefore, in order to meet the 70% recycling target, 
which will require a collection rate of 78% (Table 34-3), waste will have to be diverted from 
the planned MBT and incineration plants (as well as landfill).  

Table 34-4: Direct Inputs to Residual Waste Treatment Plants as a Proportion 
of Total Municipal Waste, 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants (a) 

Direct Inputs to Incineration Plants (b) 

Total Direct Input to Treatment Plants (c = a + b) 

Maximum Amount of MSW that can Theoretically be 
Collected for Recycling (100% - c) 

Full Implementation 

11% 

19% 

30% 

70% 

Source: European Reference Model on Municipal Waste Management. 

The model assumes that between the Full Implementation and 70% Recycling Target 
Scenarios the proportion of residual waste sent to landfill, MBT or incineration remains the 
same (see Table 7-5). This is a simplifying assumption of the model. In reality, more waste 
would probably be diverted from landfill if the other types of treatment plants were already 
constructed and locked into long-term contracts. 

Table 34-5: Change in the Treatment of Residual Waste (Direct Inputs), 2030 

Direct Inputs to MBT / Mixed Waste Sorting Plants 

Direct Inputs to Incineration Plants 

Direct Inputs to Landfills 

Total Residual Waste 

Total, % of MSW 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Thousand tonnes 

5,994 

9,733 

7,841 

2,975 

4,832 

3,893 

-3,018 

-4,901 

-3,949 

23,568 

11,700 

-11,868 

48% 

28% 

-20% 

Source: European Reference Model on Municipal Waste Management. 

28/05/2015 

447 

 
  
 
Table 26 in the accompanying Member State Data Table shows that the increase in total 
recycling from Full Implementation to the 70% Recycling Target scenario is matched by the 
total decrease in the management of residual waste.  

34.2 

Change in Waste Collection Systems 

This section provides data to explain how the types of recycling and refuse collection system 
change between the two scenarios. The approach to collections modelling is outlined in 
Section 4.0 of this report.441  Table 34-6 shows the spread of collection system types under 
both Full Implementation and the 70% Recycling Target. It is clear from this that there is a 
significant change in the recycling collection services in order to allow for the increased 
capture of recyclables.  

Table 34-6: Variation in Collection System Types under both Scenarios, 2030 

Full 
Implementation 

70% Recycling 
Target 

Difference 

Group 1 - low frequency bring / kerbside 
refuse 

Group 2 - high frequency bring / kerbside 
refuse 

Group 3 - Medium frequency bring, kerbside 
recycling + high frequency kerbside refuse 

Group 4 - Medium frequency bring, kerbside 
recycling + low frequency kerbside refuse 

Group 5 - Low frequency bring, kerbside 
recycling + low frequency PAYT kerbside 
refuse 

0 

0 

143 

1,312 

0 

0 

0 

9 

0 

0 

-143 

-1,303 

376 

1,822 

1,446 

Source: European Reference Model on Municipal Waste Management. 

34.3 

Financial Costs 

34.3.1  Costs of Waste Collection 

One of the key determinants of the financial costs of the change in waste management is 
the cost of waste collection. Table 34-7 shows some of the key waste collection assumptions 
used in the modelling.  

441 For further details see Appendix 5 of the following report: Eunomia Research & Consulting, and 
Copenhagen Resource Institute (2014) Development of a Modelling Tool on Waste Generation and 
Management, Report for European Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip 

 
 
 
                                                   
 
Table 34-7: Member State Specific Waste Collection Assumptions  

Assumption 

Value 

Unit 

Source 

Recycling Collection System Preference (all scenarios) 

Bulk collection 

Household Waste as a Proportion of MSW1 

Proportion of Households2 

Urban 

Rural 

200.0 

68 

32 

Labour Costs 

Mean Net Annual Earnings 

26,332 

Tax rate (% of salary) 

Social Security and other 
labour costs paid by 
employer (% of total labour 
costs) 

20 

13 

Eunomia / 
Eurostat 
Labour 
Costs 

Eurostat 
WStatR 

Eurostat 

Eurostat 

Eurostat 

Eurostat 

- 

% 

% 

% 

€ 

% 

% 

Eurostat 

Collection Frequencies 

Mean Gross Annual Earnings 

39,557 

€ 

Eurostat 

Food Waste Collection 

High Frequency Refuse 
Collection - no food 

High Frequency Refuse 
Collection - with food 

Low Frequency Refuse 
Collection - with food 

5.0 

5.0 

6.3 

7.5 

Days between 
collections 

Eunomia 

Eunomia 

Eunomia 

Eunomia 

Notes:  

1. Household waste as a proportion of MSW was calculated based upon data from the Waste Statistics 
Regulation. 

2. The model differentiates between urban and rural households for the purposes of calculating collection costs 
i.e. the costs of collection in rural areas are different to those in urban areas. 

Table 28 in the accompanying Member State Data Table shows the costs of waste collection 
under the Full Implementation and 70% Recycling Scenarios. This Table shows the cost of 
collecting both recyclables and residual waste for each of the five recycling systems that are 
assumed to operate under the two scenarios (see above discussion).   

28/05/2015 

449 

 
 
 
 
Table 34-8: Summary Collection Costs (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Collection of Recycling 

Collection of Residual Waste 

CA Sites 

Communications Cost 

Total Cost 

Million € 

€ 3,088 

€ 1,427 

€ 272 

€ 119 

€ 4,905 

€ 2,682 

€ 1,729 

€ 156 

€ 50 

€ 4,617 

€ 405 

-€ 302 

€ 116 

€ 69 

€ 288 

Source: European Reference Model on Municipal Waste Management. 

The revenues associated with the sale of recyclables in 2030 are summarised in Table 34 of 
the accompanying Member State Data Table. These revenues are deducted from the total 
financial costs to calculate the net collection costs presented in Table 28 of the Data Table. 

34.3.2  Costs of Waste Treatment 

For further details on the approach to calculating disposal and treatment costs please refer 
to Appendix 4 of the technical documentation which accompanies the Municipal Waste 
Management Model.442 By way of summary, the calculated costs for different waste 
treatment options are presented in Table 36 of the accompanying Member State Data 
Table. It is important to note that these costs do not represent the gate fees charged at 
these facilities, but have been calculated to represent actual resource costs, excluding taxes 
and transfers (see Section 1.1 of the aforementioned appendix for more details). 

One can see that the net costs of treatment fall from Full Implementation to the 70% 
Recycling Scenario. This is due to an overall reduction in treatment required, but also a 
switch from higher cost residual waste treatments to treatment of source segregated 
biowastes, which have a lower cost per tonne (although additional costs are incurred in 
collection).  

When calculating treatment costs there are only a few parameters that vary between 
Member States – many were kept constant for the sake of simplicity. Although national 
taxes and subsidies do vary, it is important to note that the analysis undertaken for the 
Impact Assessment was conducted as a cost benefit analysis; thus, the effect of subsidies / 
taxes was stripped out of the modelling. The revenues from electricity and heat sales do 
vary by Member State. The assumed revenues received for the generation of electricity and 
heat in the United Kingdom are shown in Table 34-9. 

442 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

 
 
                                                   
 
Table 34-9: Assumed Energy Revenues for Generators (2015 Prices) 

Type 

Value 

Unit 

Revenue from Electricity Sales 

Revenue from Heat Sales 

€ 68.84 

€ 27.32 

€ per MWh 

€ per MWh 

Source: Appendix 4 in Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) 
Development of a Modelling Tool on Waste Generation and Management, Report for European Commission 
Directorate-General for the Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-
generation-management-model.zip. 

34.3.3 

Total Financial Costs 

Financial costs in the model are made up of the costs associated with the collection and 
treatment of waste across the entire country. The total collection and treatment costs for 
the Full Implementation and 70% Recycling scenario are presented in Table 34-10 – these 
figures relate to the total financial costs in 2030. From this it can be seen that there are net 
savings to be gained in moving from Full Implementation to 70% recycling in 2030.    

Table 34-10: Total Financial Costs in 2030 (2015 Real Term Prices) 

Full Implementation 

70% Recycling Target 

Difference 

Cost Element 

Collection Costs 

Treatment Costs 

Total Financial Costs 

€ 4,617 

€ 1,974 

€ 6,591 

million € 

€ 4,905 

€ 1,519 

€ 6,424 

€ 288 

-€ 455 

-€ 167 

Source: European Reference Model on Municipal Waste Management. 

34.4 

Environmental Costs 

The key environmental assumptions used in the model are set out in Appendix 6 of the 
technical documentation which accompanies the Municipal Waste Model. Interested 
readers should refer to this appendix for more details.443 A number of the key country 
specific assumptions which have been made are shown in Table 34-11. 

443 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

451 

 
 
 
                                                   
 
Table 34-11: Key Environmental Assumptions, 2030 

Assumption 

Value 

Unit 

Marginal Electricity Grid Mix 

Gas  

Coal 

Nuclear 

Waste & oil 

Other renewables 

Net carbon intensity 

Gas  

Coal 

Oil 

Solid biomass 

Other 

Net carbon intensity 

Electricity 

CHP – Electricity 

CHP – Heat 

Heat Only 

100 

0 

0 

0 

0 

% 

% 

% 

% 

% 

400 

Kg CO2 eq / MWh 

Marginal Heat Mix 

100 

0 

0 

0 

0 

% 

% 

% 

% 

% 

Incinerator Generation Efficiencies 

200 

Kg CO2 eq / MWh 

25 

23 

48 

80 

% 

% 

% 

% 

Source: Appendix 4 and Appendix 6 in Eunomia Research & Consulting, and Copenhagen Resource Institute 
(2014) Development of a Modelling Tool on Waste Generation and Management, Report for European 
Commission Directorate-General for the Environment, February 2014, 
http://ec.europa.eu/environment/waste/pdf/waste-generation-management-model.zip. 

The calculated external costs per tonne of waste processed via different treatment 
technologies are summarised in Table 46 of the accompanying Member State Data Table. 
The external costs are shown for greenhouse gasses (GHG) and air quality impacts. As noted 

 
above, further detail and explanations about these externalities can be found in Appendix 6 
of the technical documentation which accompanies the Municipal Waste Model.444 

The change in external costs of moving from Full Implementation to the 70% Recycling 
Scenario are presented in Table 34-12. Negative values represent a net benefit to society, 
whilst positive values indicate a net cost.  

Table 34-12: Change in External Costs in 2030 (2015 Real Term Prices) 

Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Waste Prevention 

Recycling 

-€ 117 

-€ 74,879 

-€ 74,761 

-€ 549,652 

-€ 720,657 

-€ 171,005 

Open Air Composting 

€ 70,019 

€ 80,011 

€ 9,992 

In-Vessel Composting 

€ 34,851 

€ 56,807 

€ 21,957 

AD - Electricity Only 

€ 6,474 

€ 12,369 

€ 5,895 

AD - CHP 

AD - Gas to Grid 

AD - Gas to Vehicle Fuel 

€ 614 

€ 1,172 

€ 559 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

Electricity Only 

€ 229,765 

€ 156,202 

-€ 73,564 

CHP 

Heat Only 

Combustion Only 

Bio-stabilisation 

€ 12,425 

€ 8,023 

-€ 4,401 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 0 

€ 21,996 

€ 9,564 

-€ 12,432 

Biodrying with no Plastics Recycling 

€ 0 

€ 0 

€ 0 

Biodrying with Plastics Recycling 

€ 58,819 

€ 28,555 

-€ 30,264 

AD based MBT 

€ 0 

€ 0 

€ 0 

Residual MRF + Combustion 

€ 27,342 

€ 13,122 

-€ 14,220 

n
o
i
t
s
e
g
i
D
/

g
n
i
t
s
o
p
m
o
C

n
o
i
t
a
r
e
n
i
c
n

I

T
B
M

Landfill 

€ 380,823 

€ 218,223 

-€ 162,600 

444 Eunomia Research & Consulting, and Copenhagen Resource Institute (2014) Development of a Modelling 
Tool on Waste Generation and Management, Report for European Commission Directorate-General for the 
Environment, February 2014, http://ec.europa.eu/environment/waste/pdf/waste-generation-management-
model.zip 

28/05/2015 

453 

 
 
 
 
 
 
 
 
                                                   
 
Treatment Technology 

Full Implementation 

70% Recycling 
Scenario 

Difference 

Collection and Sorting 

€ 29 

€ 39 

€ 10 

Total 

€ 293,387 

-€ 211,447 

-€ 504,834 

Source: European Reference Model on Municipal Waste Management. 

34.5 

Summary of Costs and Benefits 

The net financial costs and environmental externalities of moving from full implementation 
to the 70% recycling scenario are shown in Figure 34-1 and Table 7-13. From this it is clear 
that there is a net benefit to be gained from moving towards higher recycling rates (this is 
shown by the negative cost values).  

In terms of financial costs, there are two competing costs: one from the increase in the cost 
of recycling and biowaste treatment and the other from the avoided costs of waste being 
collected and treated as residual waste. When moving from Full Implementation to 70% 
recycling in 2030 the former is always lower than the latter and hence there are net savings 
to be gained from this move. 

The modelling assumes that under Full Implementation many countries have already had to 
invest significantly in the upgrading of collection services relative to the situation they were 
in in 2011 (the latest year for which data was available at the time the modelling was 
undertaken). In moving to higher recycling rates, effectively, the capture of materials for 
recycling increases, reducing (relative to the Full Implementation Scenario) the quantity of 
residual waste requiring collection. The refuse collection service is modelled as undergoing 
two changes: first, the collection frequency falls; second, the refuse collection is charged for 
(pay-as-you-throw is implemented). The combined effect of these changes to refuse 
collection and the (related) increases in the capture of materials for recycling is that, with 
relatively small changes in the cost of delivering the recycling collection service, the revenue 
generated from the sale of materials increases (so the costs, net of revenue generation, 
decline). At the same time, the reduced frequency of collection of refuse leads to savings on 
the delivery of the refuse collection service. In summary, the effect of measures which 
encourage / incentivise the use of the services for recycling is to improve the efficiency of 
the logistics, and capture more material for recycling from each household. This largely 
explains the effect on collection costs presented in the figure below.   

In addition to the financial savings, there are significant benefits derived from the recycling 
of more material. The majority of these benefits are associated with the avoided 
greenhouse gas (GHG) emissions related to recycling, but other significant benefits result 
from avoiding GHG emissions from residual waste treatment and disposal. The benefits 
outweigh the additional emissions to air that are generated as a result of the treatment of 
biowaste and the collection of recyclables. In total, the 70% recycling scenario will have 
saved 34.2 million tonnes of CO2 eq by 2030 relative to the Full Implementation scenario.  

 
Figure 34-1: Net Social Costs – Full Implementation vs 70% Recycling Scenario 
(2015 Real Term Prices) 

Note: Positive costs denote a cost to society whilst negative costs represent savings/beneftis. 

Source: European Reference Model on Municipal Waste Management. 

Table 34-13: Total Costs and Benefits (2015 Real Term Prices) 

Costs and Benefits 

Net Costs and Benefits in 2030, 
million € 

Net Present Value (NPV), 2014 – 
2030, million € 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Full Imp. 

70% 
Recycling 
Scenario 

Difference 

Environmental Externalities 

€ 293 

-€ 211 

-€ 505 

€ 3.3 

€ 1.7 

-€ 1.61 

Financial Costs (social metric) 

€ 6,591 

€ 6,424 

-€ 167 

€ 75.8 

€ 75.7 

-€ 0.06 

Net Costs and Benefits 

€ 6,885 

€ 6,213 

-€ 672 

€ 79.1 

€ 77.4 

-€ 1.67 

Source: European Reference Model on Municipal Waste Management. 

The employment intensities – that is, Full Time Equivalents (FTEs) per tonne processed – 
associated with recycling and preparation for reuse are typically much higher than those for 
residual waste treatment and disposal. As a result, achieving 70% recycling/preparation for 
reuse in 2030 leads to an increase in employment as greater quantities of waste are sent for 
recycling. The extent to which these job opportunities will be realised in the United Kingdom 
depends on the amount of waste that is processed within the country’s borders as opposed 

28/05/2015 

455 

-€600-€500-€400-€300-€200-€100€0€10020112012201320142015201620172018201920202021202220232024202520262027202820292030Costs, Thousand €2015 Real TermsExternalitiesFinancial CostsNet Costs and Benefits 
 
 
to being exported for treatment abroad. The estimated increase in direct employment in 
2030 under the 70% recycling scenario is 27.4 thousand FTEs. Note that this is direct 
employment only with no provision for multiplier effects. 

 
  
 
FURTHER DEVELOPMENT OF 
THE EUROPEAN REFERENCE 
MODEL ON WASTE 
GENERATION AND 
MANAGEMENT 

FINAL REPORT – APPENDIX 4: LOG OF 
ACTIONS ADDRESSED ON THE MUNICIPAL 
WASTE MODEL  

Thomas Vergunst 

Dr Dominic Hogg 

Timothy Elliott 

Laurence Elliott 

Mark Corbin 

28th May 2015 

 
 
 
 
 
 
 
 
 
 
 
 
 
Report for Michel Sponar, DG Environment of the European Commission 

Prepared by Thomas Vergunst, Timothy Elliott, Laurence Elliott, Mark 
Corbin 

Approved by  

Dr Dominic Hogg 

(Project Director) 

Eunomia Research & Consulting Ltd 
37 Queen Square 
Bristol 
BS1 4QS 

United Kingdom 

Tel: +44 (0)117 9172250 
Fax: +44 (0)8717 142942 

Web: www.eunomia.co.uk 

Disclaimer 

Eunomia Research & Consulting has taken due care in the preparation of this report to 
ensure that all facts and analysis presented are as accurate as possible within the 
scope of the project. However no guarantee is provided in respect of the information 
presented, and Eunomia Research & Consulting is not responsible for decisions or 
actions taken on the basis of the content of this report. 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

1.0 

Log of Actions ...................................................................................................... 1 

APPENDIX 2  

iii 

 
 
 
 
iv 

28/05/2015 

 
 
1.0  Log of Actions 

This Appendix contains a full list of the comments that were processed and acted upon as 
part of the model revision (see Table 1-1 below). These comments were derived from 
internal discussions and were also received from the European Environment Agency (EEA) 
and European Topic Centre on Waste and Materials in a Green Economy (ETC WMGE).   

28/05/2015 

1 

 
Table 1-1: Comments and Actions Log Associated with the Further Development of the Municipal Waste Model 

Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

We expect different users to have different rights 
to amend the model. In particular we imagine that 
the final user (e.g. a MS) should not be able to 
change anything in the model with few exceptions 
(add data, scenarios, sensitivity), while the ETC 
team should be able to make some basic 
modification to the user interface (like text, labels) 
which might come to our mind after more trials 
and practice with the model itself, and also to 
modify EURM_MSWM – Calculations when new 
information becomes available. How will these 
different categories of users be defined? 

The user is often given the possibility to introduce 
own data or assumptions, but he does not have to 
document or reference any new data he loads into 
the model. Would it be possible to make the saving 
of new assumptions conditional on the creation of 
a link to a documentation file? 

This is pretty much already in the model, the 
model is 'locked down' by default and there is  
a button on the setup model sheet that would 
allow admin users to unlock the model and 
make changes. In terms of the calculations file 
this will be password protected so only Admin 
users can make changes. We will put the admin 
mode button on the home page with a short 
description. Other than that the normal user 
shouldn't have to be aware that there are other 
modes of operation. TE 05/01/2015 There are 
only two levels of users - admin, with complete 
access to edit all text and formulae, and basic, 
with access to only the user-editable variables. 
A third is seen as adding unnecessary 
complexity - inexperienced users are advised 
not to edit any formulae. 
The assumption has been that users would 
record the source of any key assumptions in an 
accompanying document, as we have done. 
Creating a 'link' might not be that helpful. If a 
link to a file on the local computer / server then 
if the file moves / is renamed etc the link will 
break. A weblink might be appropriate, but I 
think better to have a free text field next to any 
user defined data to allow the user to add the 
chapter reference of an accompanying 
document rather than the link itself. In either 
case some maintenance will be required. We 
will add in a text field, and you can decide how 
best to use it and communicate it to users. TE 
05/01/2015 

28/05/2015 

1 

OK, we have no further 
comments. 

Is it possible to imagine some 
mechanism to make this 
process mandatory to users? 
Can the model, for instance, 
give an error message if an 
user is not adding the 
references in the text file? I 
think we should imagine some 
mechanism to track these 
kind of changes 

difference check put into 
results sheets 

 
  
 
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

Text fields added to "define assumptions", 
"waste arisings projections" and "set up waste 
prevention" sheets.  LE 19/01/2015 

Difference check added that informs the user 
whether new user-defined assumptions have 
been entered (i.e. whether there are now user-
defined assumptions that are different values 
to the default assumptions). This is in 8. Model 
Outputs sheet. Does anything else need 
doing?? LE 06/03/2015 

When there is an accounting identity between two 
ranges of data (i.e. both ranges should be –
approximately- equal), will the user receive an 
error or warning message if the data he enters are 
inconsistent with this identity? 

Not sure what this means, can you provide 
some additional information example etc? TE 
05/01/2015 

Suppose that we have 5 
variables A, B, C, D, F, and 
mass balance requires that A 
+ B = C + D+ F. There are 
several reasons why, in 
practice, this equality does 
not hold in the calculations. 
For instance, it is possible that 
data on these variables come 
from different sources (who 
may use different units 
without documenting them), 
and that the user introduces 
some data with the wrong 
units. Or the user may simply 
mistype some input values. If 
the difference between A+B 
and C+D+F exceeds some 

TE - as discussed we have done 
this but need to make the 
checks more visible to the 
user, or at least visible if they 
do not balance. We have also 
added in a check when the 
model runs, if the mass 
balance checks are out it flags 
this. The results of the mass 
balance checks can be viewed 
on the Summary of Cross-
checks sheet in the calculations 
file or in the results file. Topic 
centre to check again when 
implemented. 

 
 
Comment 

Eunomia Reply 

Discussed at Meeting 17.02.15 

Further response from Topic 
Centre 
threshold (e.g. corresponding 
to reasonable rounding 
errors), then an error 
message or at least a warning 
should be issued to the user. 

It is, in most cases, possible to set a step as 
complete without making any changes to the page 
(which may be OK if there is no need to update 
data). If you set a step complete by mistake, is 
there any possibility to set it incomplete again? 

If the step is set complete, it seems that it is still 
possible to make changes to the page without 
getting any notification.  There is a risk that 
somebody makes, by mistake, changes to the page 
that is completed– what would this imply for the 
model runs? 

Costs and benefits are currently expressed in EUR. 
How can non-EURO countries save the exchange 
rate they have used for user-defined assumptions? 

We didn't want to constrain the model too 
much, the buttons were more to get users to 
think about the steps they might need to take 
and to recognise when they thought they were 
complete. The model will still run with no 
changes to the default setup, but just only with 
the three default policy scenarios. 
 We had planned to toggle the step complete, 
but didn't get the chance in the end. We'll 
change the functionality / button headings 
accordingly, so that the user can set to 
incomplete if they desire to. TE 05/01/2015  
Changed to enable users to mark stages as not 
complete MC 07/01/2015 

ok, we'll add in some controls to set the page to 
incomplete if any of the data changes. TE 
05/01/2015  Added code at worksheet level 

We only ask for inputs as € as far as I can 
remember. We assume any exchange rate 
calculation is done outside of the model and 
recorded there, and likewise and conversion of 
model results is exogenous to the model. I'd 
prefer to leave it this way and not add extra 
functionality to the model to allow for national 
currencies as it will clutter up the UI a bit, but if 
you think essential we can discuss. TE 

again, this is an issue of 
traceability and 
reproducibility. All raw data 
and all assumptions should be 
contained in a single model. 
Spreading data and 
assumptions over different 
files can only lead to 
confusion. 

Can probably do something 
relatively easily actually. 
1. put in a control on the set up 
model page, allow the user to 
select EUR or the national 
current code. Take exchange 
rates from eurostat and put at 
top of define assumptions 
sheet to allow users to changes 

28/05/2015 

3 

 
  
  
  
  
Comment 

Eunomia Reply 

05/01/2015 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

them. like the deflator 
2. make all section headings 
with € in a formula that picks 
up the currency code that is 
selected. 
3. for default assumptions just 
multiply the incoming 
reference by the exchange rate 
4. for UD assumptions the 
multiplication needs to be 
done in the assumptions data 
store sheet which refs the DA 
sheet 
5. change source to Source / 
Currency: for any financial 
data. 

Tim - I have done this for the 
define assumptions and set up 
a decent interface for the user, 
I have changed the headings 
and also put the relevant data 
validation in a datastore and 
changed these values. I just 
realised that it also needs to be 
done for the Set Up Waste 
Prevention and Sensitivity 
Analysis sheet. The cells in the 
calculations sheet that link to 
these sheets will need to be 
changed to make sure the 
exchange rate is factored in. 
The model always uses the 
Named Range 

 
 
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

"ActiveExchangeRate" (this is 
set to 1 if using Euros). 
Exchange rate also needs 
adding to 8. Full Model 
Outputs sheet 

• Exchange rate, change all 
array formulas in results 
overview sheet so they add in 
the exchange rate. Add box at 
top – select currency for 
results (two options). And get 
rid of Euro formatting 
o Vertical axis of charts make 
sure real terms year and 
currency code 
o Set up Waste Prevention – 
cut to right do conversion and 
hide columns 

• Set Up Sensitivity – these 
values are always pulled 
through in Euros so convert to 
whatever currency. 
Underneath table add currency 
as a footnote 
o F24 put in “Note: Financial 
figures are displayed as EUR” 
o Check sensitiviery outputs 
with Mark 

28/05/2015 

5 

 
 
 
Comment 

Eunomia Reply 

Suppose that the user introduces numbers, that, 
from the context, are obviously wrong (for 
instance, because he uses an incorrect unit to 
introduce his data)  - could a warning message be 
issued? 

We have put in some controls to stop text 
being entered into numerical fields > 100% < 
0% checks on percentage inputs and upper / 
lower bounds in all the user defined 
assumptions. I think this should be enough 
unless you have any specific examples for us? 
How would you check for an incorrect unit, 
what exactly do you mean here, kt rather than 
mt or something? TE 05/01/2015 

Discussed at Meeting 17.02.15 

complete 

Further response from Topic 
Centre 
 This is indeed what we had in 
mind. The use of wrong units 
occurs very often and can 
have dramatic results (space 
missions failed because of 
that  
http://articles.latimes.com/19
99/oct/01/news/mn-17288 ). 
There are cases where the 
developer has a good idea of 
what a "reasonable" value 
should like (for instance, from 
previous observations of the 
same variable). It would 
clearly be very difficult to be 
exhaustive, but some checks 
of crucial variables could go a 
long way. 

The buttons at the bottom and top of the page 
(“Next step” and “Mark step complete”) 
sometimes react when clicked on, sometimes they 
don’t. We have not been able to find any system in 
this, so we suppose that this depends on the 
fulfilment of conditions that are hidden to the user.   

They all work fine on our version, there are no 
conditions that have to be met for the sheet to 
move forwards or the step complete message 
box to appear. Check out the macros if you 
want to see what they do. If this problems 
persist it might be worth doing a remote 
session and you run through what you are 
doing with us looking at your screen from this 
end. TE 05/01/2015 

Such a remote session would 
probably be a good idea 

complete 

 
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

It is still possible to run the model without 
completing the “set up” steps. It is also possible to 
mark a step as “complete” without marking the 
previous steps as complete 

When we mark a step as “complete” and then load 
the data for a new MS, the step remains marked as 
complete. This remains true when we save, close 
and re-open the file. 

We have been on several occasions able to modify 
the contents of “calculation cells” or “read-only 
variables”, and to mark the step as complete 
without even receiving a warning (at least in the 
sheets “Annual Update” and . “Define 
Assumptions”). 

Yes we didn't have time to do that. We will add 
a control that stops the model running unless 
all the steps have been marked as complete. 
We don't see it as necessary to complete the 
steps in order, in fact it is more flexible if the 
user can dip in and out, so we won't make any 
change here. Also as your comment doesn't say 
'steps should only be followed and marked 
complete in the order implied in the model' TE 
05/01/2015 Added check to run model macro:  
Check, or disallow? MC 15/01/2015 
For the first point we didn't add any 
functionality there as it is mainly used as a one 
country model so users won't be flicking 
between countries, and if EEA then the model 
would probably be set to EU-28. Regarding the 
second point it seems sensible to me for the 
marked steps to be saved when the file is saved 
closed and reopened, otherwise the user would 
need to do this each time the file opened. Do 
you agree, if not what is the specific issue with 
the current operation and the specific change 
requested? TE 05/01/2015  The steps change to 
incomplete whenever a value in that sheet is 
edited. MC 
I don't think we set all the cells to locked in the 
version you sent, but we have now locked 
down all calculation or read-only cells so they 
cannot be edited anyway. As noted above if a 
user defined assumption is changed we will 
mark the step as incomplete. TE 05/01/2015  
There are still problems with getting the 
macros to run properly on the protected sheets 
MC 15/01/2015 

28/05/2015 

7 

OK, we have no further 
comments. 

I can foresee a user (for 
example EEA) to run several 
countries and possibly test 
things without wanting to 
save several files. Suggestion: 
when the country is changed, 
the marked steps change back 
to incomplete.  

 
  
  
  
  
Comment 

Eunomia Reply 

If an Excel workbook is opened in a different 
language version than the one in which it was 
written, this could create compatibility problems. 
Has this possibility been considered? 

We understand that the Excel workbooks that will 
be distributed to the member states will be “read 
only”. However, we understand that, in some 
cases, it is possible to overrule this restriction if the 
workbook is opened in Open Office or Google 
Sheets – have safeguards been included to prevent 
this from happening? 

I'm not sure what problems you are referring to 
as we haven't come across this problem. Can 
you give us more details of what problems you 
have encountered / the model might 
encounter? TE 05/01/2015 I'm not sure we 
should be trying to speculatively address all 
problems that existed with previous versions of 
Excel. We should state minimum requirements 
rather than make fully back compatible. TE 
16/02/2015 

We are checking this out. Can Google Sheets 
open .xlsm files with macros in anyway? Good 
point though as the more secure controls as set 
during a start-up macro, the normal password 
set by making the file read-only is pretty easy 
to break anyway, but we just need to check 
what happens with these on-line version. To be 
honest one could probably 'crack' any excel 
files if one so wished. I think we have to think 
about proportionality, the 'locked' parts of the 
workbook are to stop users inadvertently 
messing it up, not to provide a high level of 
cyber security, I guess we have to trust the 
member states a little. If the EEA want zero risk 
that the member states can access and alter 
the underlying code then sending out excel 
files, locked or otherwise, would presumably be 
out of the question and therefore an on-line 
database solution would have to be found. TE 
05/01/2015 

Discussed at Meeting 17.02.15 

comment made about, English 
and pc, minimum 
requirements on model home 
page 

Further response from Topic 
Centre 
In earlier versions of the finish 
excel version, there were 
some issues with not-properly 
translating of excel functions, 
and the models did not work. 
Opening the model with the 
Italian excel version seems to 
work so far.  Here's an 
example of issues that can 
arise 
https://groups.google.com/fo
rum/#!topic/microsoft.public.
excel.misc/sZyxIxcwtjI . 

I wouldn't assume that users 
would commit deliberate 
fraud either. The concern is 
either inadvertent overruling 
controls 

test with open office, comment 
about note using google sheets 

 
 
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

Tried to open model in open office, waited 20 
mins and the file still hadn't opened! Doesn't 
look like it will work in open office. LE 
20/02/2015 

This looks like it might be possible but I don't 
think it would be possible to build in 
safeguards. Perhaps worth checking out 
ourselves using openoffice/google sheets? LE 
15/01/2015 

Tim is going to clarify with EEA what their main 
concerns are i.e. we doubt the model would 
run properly in open office or google sheets, is 
the main concern that users may try to 
fraudulently obtain hidden data from the 
model? LE 19/01/2015 

LE to check what happens if we try to open in 
google sheets. If not a fraud issue then al we 
need to say is don't use google sheets etc. 
Comes back to the minimum operating spec 
mentioned above. As long as we say what 
should work fine, it is the users risk if they 
chose to use some other configuration. TE 
16/02/2015 

Tried to open the file in open office but after 
waiting for 20 mins the file had still not opened. 
The file is too complex to be used with open 
office. LE 19/02/2015 
Yes, they are in the datastore, they can be 
edited there directly or we could perhaps take 
off the edit restriction once the view in admin 

Can the administrators of the model edit the 
default projections present in the model? 

28/05/2015 

9 

This again raises the issue of 
keeping track of changes 
through time, version control 

will add change log as per calcs 
file, ok for the moment 

 
 
 
 
 
Comment 

Eunomia Reply 

mode button had been pressed. I would say the 
former would be easiest, once you know where 
to look it is quite straightforward. TE 
05/01/2015 

We will add in an admin version control sheet 
like in the calculations file that stop you saving 
it before confirming that you have updated the 
version control log. Is this ok? TE 16/02/2015 
Ann did this, she said there are potentially 
100's of MBT plants, for example, but she did 
some research looking at general types in the 
different countries, on that basis developed 5 
types that covered the general patterns. The 
approach could be summarised as expert 
judgement based upon some literature review, 
but not with an detailed quantitative options 
appraisal. Biowaste - from biowaste IA study. 
Biorefineries and other novels types not looked 
at as, realistically, won't be commercially 
available and widespread beyond lifetime of 
model and no idea about costs so would be a 
difficult guess. TE 05/01/2015 

It would not be possible to add in an empty 
model. There are so many interdependencies 
from the mass flows to env impacts, financial 
costs etc. It is a big task to set this up correctly. 
The 5 representative models are fine for a 
model which is fairly high level like this one. TE 
16/02/2015 

Which criteria have been used to determine the 
technical options for waste management that have 
been included in the scenarios? Have some 
technologies been considered but discarded after 
further analysis, for instance because they were 
not deemed mature enough (for instance, 
biorefineries)? 

All text boxes need to be read-only cell for the final 
users. 

ok, agreed TE 05/01/2015 

Discussed at Meeting 17.02.15 

won't do this - complete 

Further response from Topic 
Centre 
etc. How can we keep track of 
why changes have been 
introduced, who dit it, when 
he dit it, why he dit it? (in 
version control systems, you 
cannot commit a new version 
of your model unless you 
comment why you introduced 
the changes you did) 

Would it be possible to add a 
6th type which is user defined 
and "empty" in the delivered 
model? Giving a constrained 
set of inputs needed to 
calculate and link everything 
in the model properly would 
be enough and give MSs and 
other users possibility to 
explore potential of other 
types. 

 
 
 
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

Due to the large number of sheets, the user cannot 
even see all sheet tabs and finding some specific 
sheet becomes difficult – e.g. having a link to the 
“home”-page on every sheet and a link list to all 
the sheets on “home”-page might help to navigate 
in the workbooks (on some sheets buttons can be 
used to navigate, but this is not always the case). It 
is also confusing to give the user the opportunity to 
start from any sheet after opening the workbook. 

In addition to “basic view”, one can choose 
“advanced view” and “admin view”. What are the 
differences between these views? How can we 
obtain the password? Who would set the 
password? 

The aim is to take out the tab headings anyway. 
As a consequence the model has the consistent 
menu bar on each page to the right with a 
home page button. This menu bar allows the 
user to access all the visible sheets on the 
model, so I think the first point is already 
addressed, unless there are any other specific 
comments? 
Regarding the second point there is a control in 
the open macro that takes the user to the 
home page, this might not have been set in the 
previous version - MARK - check this out please. 
TE 05/01/2015 checked 15/01/2015 

We have put in the model overview 
information in the calculations file. TE 
16/02/2015 
There is no password set you just hit the ok 
button. This is basically unlocking the workbook 
but when we locked it we left the password 
blank so this means there is no password set. If 
you want to set a password you just need to 
use the normal Excel function for locking the 
workbook but put in a password, then you will 
have to enter the same password when the 
code calls the unlock function through the 
macro attached to the Admin button. Is this 
enough info? TE 05/01/2015 You are asked to 
set a password when you lock the model, which 
you are requested for when you unlock it and 
switch to admin mode.  If provided protected, 
the password in use will be "EURM" MC 
15/01/2015 
None - advanced view removed MC. This is now 

And what about the 
calculations workbook? There 
the issue of the lack of 
overview is much more 
pressing. 

And so what is then the 
difference between "basic" 
and "advanced" view? 

28/05/2015 

11 

 
 
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

pick up later with LF 

Nothing happens when I click on “Click for 
administrative access to the model - password 
required”. It is thus not clear whether I have run 
this model as “administrator” or as “normal user”.  
We suspect that in the second box there is an 
orthographic mistake: instead of “It model is also 
intended to act as a 'early warning system' for 
…”The model is also intended to act as a tool in the 
early warning procedure for...” 

What is the “EU operating method”? What does it 
mean “not to refresh the data”? Please clarify 
when this box should be ticked. 

addressed there is normal operating mode and 
admin view only. TE 16/02/2015 
Works fine on our version. TE 16/02/2015 to 
check with them. Have changed formatting of 
box - the button works ok on our version MC 
18/02/2015 

 Updated. 

When in EU mode the policy scenarios that one 
sets up are non-country specific and are copied 
to all EU-28 countries when the model is run. It 
also means the EU-28 results will run not an 
individual country's if this mode is selected. We 
will add a text box to describe what EU-28 
mode is. 
The don't refresh data was if you wanted to 
change between countries quickly perhaps to 
change the policy scenarios without having to 
open the calculations file, this saves time. It 
might not be that necessary so we will either 
remove it or add some guidance in the form of 
a text box. TE 05/01/2015  Add EU-28 button, 
remove check-box and update the macro 
assigned to changing country as doesn't need 
to open calcs file.  Repoint the latest year data 
throughout model to datastore MC 
09/01/2015. Do we need to add a password to 
this box? MC 15/01/2015 

Suppose that the user introduces numbers, that, 
from the context, are obviously wrong (for 
instance, because he uses an incorrect unit to 

See response above, not sure why this 
comment appears under the setup model 
section as there is no data the user can change? 

I imagine is the same 
comment as line 9 

 
  
  
  
  
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

introduce his data)  - could a warning message be 
issued? 

TE 05/01/2015 

We have been able to mark the step ““Annual 
Update” as complete, although we had updated 
2012 before 2011 (and the instructions say that we 
should first have entered the data for 2011). See 
hereunder: 

See Screenshot 1 

When we subsequently click on “update annual 
data”, this  is followed by the following error 
message, but it is not clear whether this is related 
to the mistake described above:  

See Screenshot 2 
We recall from previous correspondence that the 
“annual update” sheet in “EURM_MSWM - 
Controls and Outputs” enables users to save their 
updates in a data sheet in the “EURM_MSWM – 
Calculations” workbook.  

You had mentioned that it may be possible to 
restrict “country users” to updating data only for 
that country. However, we think that users should 
not be given any opportunity to write to the 
“EURM_MSWM – Calculations” workbook, as this 
could lead to huge mistakes. Would it be possible 
to save “updated data” to a separate file instead, 
where the name of the file refers clearly by whom 
and when the file has been created and/or edited? 

If the creation of such a separate file with user 

check this, should have to do each year 
consecutively. TE 05/01/2015. The model is set 
up so that years can only be updated 
consecutively. It is possible that you were able 
to update 2012 before 2011 by entering in a 
year manually - this is no longer possible as the 
cells that calculate/display the update year are 
read-only. LE 14/01/2015 

How much data is actually being stored? I'm 
wondering whether we move the waste flow 
data to the control and outputs, have a 
streamlined datastore like marks, this will 
remove 29 sheets from the calcs file. TE 
05/01/2015  Am I correct in thinking that the 
macro only ever adds data - or can you reload 
data from previous years?   how much data is 
actually being edited by the annual update 
macro.  MC 07/01/2015 

The annual update no longer writes data to the 
"EURM_MSWM - Calculations" workbook. 
Instead, data is saved to a separate datastore 
sheet ("Historic Data Store") in the 
"EURM_MSWM - Controls and Outputs" file. 
Whenever data is updated a record is made in 

28/05/2015 

13 

 
 
 
 
  
  
 
 
 
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

updates would not be feasible, then it should be 
possible to trace by whom and when changes have 
been introduced to the “EURM_MSWM – 
Calculations” workbook. Moreover, the user 
should be warned that he is writing to 
“EURM_MSWM – Calculations” workbook 
(“loading the data in the model” is ambiguous)? 
What if “EURM_MSWM – Calculations” workbook 
happens to be open (maybe inadvertently) and the 
user does not save? What if the user has already 
saved the data and another user modifies them 
(for instance, if the file is kept on public folders)?  

It is currently possible to mark this step as 
complete without clicking on “Update annual 
data”. What is then the meaning of “having 
completed the step”?  

the "Historic Data Store" sheet of the username 
(of the windows user making the update) and 
the date and time of the update. LE 14/01/2015 

It might be difficult to automatically judge 
when data is out of date, so we didn't want to 
constrain the control in this way. As mentioned 
above the purpose of the steps was to make 
sure someone had at least thought about 
whether the data needed updating or not 
before they pressed the model run button. 
Given the couple of comments about this I 
think it might be better to name the button 
'Step Checked' / 'Step Not Checked'. This 
implies more clearly that for some steps no 
action might be necessary. Whilst writing I also 
think that I will put in a text field which records 
a date stamp and the windows user who 
pressed the step checked button, for greater 
clarity in future audits. Are you happy with this 
proposed approach? TE 06/01/2015 

A text box has been added to the 6 sheets, this 
records the windows user and a date stamp 
whenever the step checked button is pressed. 
The button has been renamed "Mark Step as 

Adding a date stamp would be 
a step forward, that's sure 

 
 
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

It is possible to modify the “user defined vales” for 
“post-MBT” waste, even when the option “default 
values” has been chosen. Should not this table be 
hidden when the default values are chosen? We do 
get the following error message when we click on 
“Update annual data”, but we do not know 
whether this is linked to the previous error 
(something similar happens when we change the 
default values): Screenshot 1 

When we have 2011 as “Latest year of actual data 
in model”, and we introduce fictitious data for 
2011, we get a message that these data are 
suspicious, but not that we are overwriting data 
that are already in the model: 

What, if for some reason, more than two years of 
data should be updated? Should we then first 
update the model for 2011 and 2012 (for instance), 
save this to the disk, and then perform the update 
for 2013 and 2014?  

Checked"/"Mark Step as Not Checked". 
14/01/2015 
ok we will address this first point. The error 
should be fixed, make a note to double check 
once the revised version is sent over. TE 
06/01/2015. The "user defined" values for 
"post-MBT" wastes are now hidden when the 
"default values" are chosen. The error probably 
occured due to entry of data into cells which 
are now locked as read-only cells - so the error 
should not occur again.  LE 14/01/2015 
ok, we will add a message box saying that the 
data will be overwritten and do they want to do 
that. TE 06/01/2015 

Data cannot be overwritten because the 
update year is automatically loaded and cannot 
be changed by the user - the update year is 
always one year after the latest year of data in 
the model. The user may have been able to 
overwrite data previously due to cells that 
should be read-only not being locked - these 
are now locked. LE 14/01/2015 
yes, do one year first then the next. We will 
make it clearer in the guidance somehow. TE 
06/01/2015 

I have made it clear in the guidance that it is 
necessary to update one year first and then the 
next. LE 14/01/2015 

28/05/2015 

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Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

When we put the total amount and percentages 
into the Overall generation and treatment shares 
table, and values in the recycling table, the model 
seems to update, but the numbers are lost from 
the page and setup page shows no update. Is it 
because we first tried Eurostat converter, which 
did not update but gave error message? 

When we update the data in the “annual update” 
tab, the status in the step 1 of tab “set up model” 
shows the correct label “complete” but the last 
available year still remains 2010 (even if we 
correctly uploaded year 2011). This is misleading 
(see picture below): 

Screenshot 4 

Similarly, also the tab “Annual update” is not 
automatically updated (we expect it should change 
in something like latest year of actual data in the 
model 2011 – year to update 2012) 

Screenshot 5 

“Depending on how many years have elapsed since 
the last annual data input”: suggestion to modify 
this to “Depending on how many years have 
elapsed since the last annual data input by the 
administrators of the model”. 

“It is possible that the Eurostat Data Converter can 
calculate negative values for the quantity of waste 
going directly to landfill or incineration”: it would 
be helpful to explain to the user why this is 
possible.  

I suspect yes because there was an error. We'll 
double check the functionality this end, and 
you can do the same when you get the revised 
version. TE 06/01/2015 

The functionality has been checked and this 
error message will no longer happen. LE 
14/01/2015 

it should update we will check and fix any 
issues. TE 06/01/2015 

The functionality has been checked and this 
error message will no longer happen. LE 
14/01/2015 

I'm not sure this is necessary the model user 
can update the data as they go, you (EEA / 
topic centre) are administrators only, not the 
member states. Suggest no change, please 
confirm or give further reasoning. TE 
06/01/2015 

ok we will add further information. TE 
06/01/2015 A box has been added to the 
"annual update" sheet to explain to the user 
why. LE 16/01/2015 

Ok for the formulation as it is 

 
 
  
  
 
 
 
 
  
  
  
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

Tip collection rate in manual update: “The 
collection rate needs to be decided depending 
upon the presence of MBT in the country and the 
general development of waste collection services, 
not simply generation minus treatment” – This 
sentence is not very clear. 

It is still possible to have total treatment shares 
exceeding 100% (although the user does get a 
warning). What impact does it have on the model 
results if the actual sum exceeds 100% (for 
instance, due to rounding errors)? (screenshot 16) 

I do not get an error message when the total 
amounts collected for recycling per subcategory 
exceed the amounts implied by the share of 
“collecting for recycling” in total waste generation 
(screenshot 16) 

ok we will revise the sentence. TE 06/01/2015 

Ok, we'll add in a macro that checks the value 
of the sum cell each time any of the above cells 
in changed. TE 16/02/2015 

The data validation has now been fixed so that 
the user is no longer able to enter total 
percentages above 100%. The 'sum' cell now 
turns green once the input cells total 100% to 
inform the user that they have succesfully 
inputted treatment shares. A check has been 
added so that when the 'update annual data' 
button is pressed a message box pops up if the 
percentage is not equal to 100% - the annual 
update cannot proceed until this is fixed. LE 
17/02/2015 
ok, we'll add in a macro that checks the total is 
not greater than total generation. I noticed you 
also put the data in the greyed out box cells 
rather than the white input cells. We'll consider 
something to stop the user doing this as well. 
TE 16/02/2015 

A data validation has been added so it is now 
impossible for the user to enter recycling 
tonnages for individual waste streams whose 
sum exceeds the total amount of waste 
generated. LE 17/02/2015 

28/05/2015 

17 

 
  
  
 
  
  
 
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

Make checks more prominent 

In the Eurostat converter mode, the model 
compares the data input for 2011 with the data 
input for 2010 for consistency. However, the 
verification of the consistency of the data input by 
the user for 2010 with the data that are already 
present in the model only takes place from line 147 
in the sheet. This verification requires an active 
check by the user, but no warning message is 
issued to the user if his data are obviously wrong 
(for instance, the user may have inadvertently used 
data from a different country), see the example 
below. It is already an improvement that the 
verification does take place, but it should be more 
prominent, so that the user cannot overlook that 
something went wrong in the data input before he 
moves on. Would it for instance be possible to 
create a pop-up Window if the user tries to update 
the annual data and/or mark this step as complete 
without first confirming that his data input is 
correct: (screenshot 17 and 18) 

For MBT input: please clarify that corrections 
should be based on national (or other) sources, not 
Eurostat sources. 

I can still modify the “default” values for the post-
sort / stabilisation waste from MBT plants (but 
then it is not clear to me whether I am logged in as 
administrator or user). Same remark applies to the 
default values in the “Define Assumptions” sheet. 
Same happens with the Baseline Policy Scenario 
(although, in this case, I get an error message when 
I try to save the scenario – I suppose this should be 
enough to keep this step “fool-proof”).  

Surely the checked button is this confirmation 
that the data is correct? TE 16/02/2015 

The annual update page has been consolidated 
and additional checks put in place. All 
processes are now laid out in a linear step-wise 
fashion, and the data checks are included in 
this step-by-step flow. Two additional pop up 
message boxes have been built in. These inform 
the user of 2 sources of incorrect data - suspect 
eurostat data and treatment shares not adding 
up to 100%. These will pop up when the final 
"update annual data" button is pressed. LE 
17/02/2015 

ok, will do. TE 16/02/2015 

Additional text added to guidance in annual 
update sheet. LE 17/02/2015 

I think you were just in user mode, is definitely 
locked when set to admin in our version. TE 
16/02/2015 

 
 
  
 
  
  
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

It is possible to mark the step “annual update” as 
complete even if most data have not been filled in.  

This is just a check, it maybe you don't want to 
update any data, not a strong control. Better 
this way otherwise the model will not be as 
flexible as one might want it. TE 16/02/2015 

How are the recycled tonnage calculated when 
using the Eurostat converter? 

We do need some more clear description of 
how this works. TE 16/02/2015 

we will describe this and topic 
centre to review 

This has no be completed. 
Extra sheet added and link 
from annual update sheet 
made. 

When the user introduces his own assumptions in 
the “Assumption set”, we understand that these 
user specified assumptions are not saved to a file, 
are they? If we are not mistaken, it is a parameter 
of a policy scenario whether user supplied data 
have been used, but it is not logged whether the 
user uses his own data. Thus, depending on the 
assumptions used, one scenario can mean different 
things. How can we trace which values have been 
used to run a given scenario? After all, a user could 
run the model several times, each time with a 
different set of “user defined” assumptions.  

Would it be possible to save the “user defined 
assumptions” to the disk and to link the name of 
the scenario to the file with those user supplied 
assumptions? 

We record the assumption set used and all the 
user defined assumptions for each model run. 
They are stored in the Scenario X Results sheets 
below the results. The headings / formatting is 
missing but in principle the functionality is 
there already. We will also add time / date of 
the model run and the name of the current 
windows user for greater traceability. TE 
06/01/2015 

Assumptions are now clearly stored in the 
model results file. TE 16/02/2015 
I think the above answer already covers this 
point. What we will probably do though is 
export and save the results / user defined 
assumption for each model run. This will stop 
the control and outputs file getting too big as 
well. TE 06/01/2015 

 Adding assumptions used to 
the results seems an 
acceptable compromise 
(certainly taking into account 
that the results can be saved 
to the disk), but this should 
then be better structured and 
documented. 

28/05/2015 

19 

 
  
  
 
  
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

How could we, in the future, add new fuels to the 
electricity mix when they become relevant (such as 
shale gas)?  

The user can modify the assumptions regarding the 
capital costs and the operating costs, but how can 
the user be sure that his method for calculating 
these costs are consistent with the method used in 
the model? Maybe the user has some information 
on some specific components of these costs (for 
instance labour costs) that he would like to 
customize, but without modifying the other 
components. How could that be done? 

You would need to add extra lines in the 
calculations file for % share and the carbon 
intensity and change the formulas that 
calculate the net carbon intensity of the grid so 
that the new rows are included in the cell 
references. If you need further information it is 
probably easier to walk it through over the 
phone. TE 06/01/2015 

This would be done in the calculations file by an 
admin user. We can talk through how during 
the call. TE 16/02/2015 
Regarding the unit capital costs what method 
of calculation are you referring to, this is a fixed 
assumption? I guess the scope of the capital 
expenditure could vary, handling equipment, 
buildings etc, but the fact that this might be 
unknown (although should be document in the 
report) is why the user can add in their own 
capital cost figure. There is no input for 
operating costs only TOTAL unit cost under the 
private metric, a figure more similar to a more 
familiar 'gate fee'. Again the point is that the 
user can come up with their own calculation 
methodology and therefore it is implicit that it 
would be different from the default 
methodology. We don't see a problem with 
this. TE 06/01/2015 

We haven't made all financial assumptions 
available to the user. All costs are entered in 
nominal terms and converted to constant 
prices in the model unless otherwise stated. TE 
16/02/2015 

Maybe this is something that 
should be put on the agenda 
for a next training session. I 
am not sure this should be 
done in the "Controls & 
output" workbook. 

we will write guidance on this 

Actually, this is a rather 
fundamental problem. If a 
user uses different figures as 
the default ones, it is 
important to understand why 
they differ. Fixed and variable 
costs should be broken down 
in as much as detail as 
possible to ensure consistency 
across different data sources. 
E.g. are figures expressed in 
nominal or constant prices. 
Also, it is possible that the 
user has specific information 
on some components of the 
costs (e.g. labour costs) but 
prefers to use the default 
values for other components. 

We have looked at this again 
and think adjusting the 
collections/treatment plant 
labour rates would be difficult 
as we use benchmarks then 
pro rate them using national 
labour rate data. Capital will be 
the most sensitive parameter 
which is included in scope, but 
it would be a lot of work to 
allow the user to vary each 
individual parameter, so we 
are not proposing to do this. 
We will add some intermediate 
outputs from the financial 
costs module to users can see 
what the breakdown of the 
unit costs would be. TE 
05/03/2015 

 
 
 
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

How do you define “Bring site vehicles”? 

Could you define the difference between “bring” 
systems  and “CA systems”? (We know you 
clarified the difference during the training session, 
but the Excel sheets should be self-documented).  

“Proportion of total housing stock which are flats”: 
how do you define “housing stock”? Does this refer 
to the number of buildings (independently of the 
number of households living in the building)? Or 
does this refer to the number of households living 
in flats?  

What are the differences between the “reject 
rates” per individual material, versus “Reject Rates 
from Sorting Plants, Dry Recyclate, %”? 

If a country doesn’t have a kerbside sort collection 
system, what would then be a user defined system 
and where can it be described?   

Bring site vehicles are those that collect igloos 
or other communal containers. Reading the 
report should familiarise the user with these 
terms, but we can add a clarification to the 
sheet. TE 06/01/2015. Clarification added to 
the sheet in a text box. LE 16/01/2015 
Ok we can, but the user will still need to read 
the report for the detail, we can't expect to 
have all the information available in a technical 
appendix in the excel file. TE 06/01/2015. 
Clarification added to the sheet in a text box. LE 
16/01/2015 
Housing stock is number of dwellings not 
number of buildings. We can get the metadata 
from the source and add to the sheet for 
clarification. TE 06/01/2015 

This is the number of households which are 
flats, not the number of dwellings. This has 
been added to the sheet for clarification. LE 
17/02/2015 
The material specific rates affect the mass 
flows whereas the generic ones were for the 
calculation of the costs. There were put in at 
different stages of model development. On 
reflection I think we can calculate the 
aggregated figures from the material specific 
ones, so we will do that in the model and 
remove the latter rates from the user defined 
assumptions sheet. TE 06/01/2015 
If there is no kerbside they why would the user 
try to change the rates? I don't see this as a 
problem, but perhaps you can explain the 
issues you have in mind? TE 06/01/2015 

28/05/2015 

21 

Please do 

add text boxes 

Please do 

Got an answer from Ade just 
need to think about it and do 
this 

trace formulas - probable that  
“Reject Rates from Sorting 
Plants, Dry Recyclate, %" is 
only used for calculation of 
collection income (i.e. waste 
collectors do not get income 
for rejects). 

Maybe this something we 
should discuss over the phone 
or during a training session. 
Right now, I am completely 

To be picked up with LF 

 
  
  
 
  
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Eunomia Reply 

Further response from Topic 
Centre 

confused about what this is 
supposed to mean 

Discussed at Meeting 17.02.15 

What is the meaning of the cells “Waste Prevention 
Effects, kg per household”? Is this related to the 
waste prevention scenarios defined elsewhere? 
What is meant by “Waste prevention type”?  

Are the “total capital costs” represented on an 
annualised basis or as a NPV in a given year?  

Are taxes included in the social metric? 

No this relates to the waste prevention effect 
one would likely see when new collection 
systems are rolled out to householders. We'll 
add a clarification to the sheet. TE 06/01/2015 
Clarification added in text box. LE 19/01/2015 
Neither they are the non-annualised non 
discounted total cost of the project per tonne 
of input capacity. We'll make a clarification so 
the users are sure. TE 06/01/2015 Clarification 
added in text box. LE 19/01/2015 

The input is total investment divided by 
capacity. This is then annualised using the 
WACC to aggregate with annual operating 
costs, all on a per tonne basis. This unit cost is 
then multiplied by the total tonnage treated to 
give the total cost. TE 16/02/2015 

Intermediate outputs are now provided in 8. 
Full Model Outputs sheet. LE 20/02/205 
No, this is clearly described in various places in 
the report, but we can add to this sheet just to 
be sure. TE 06/01/2015 Clarification added in 
text box. LE 19/01/2015 

Not sure what this means. Do 
you mean that this is just the 
initial investment amount 
divided by capacity? But, if 
you want to compare fixed 
and variable costs, then you 
have to express them on the 
same basis (for instance, 
taking the annuity value of 
the capital investment)? This 
point is relevant and need to 
be clearly specified. 

Topic centre to check again, 
look at report, maybe put 
some further description about 
how the financial costs are 
calculated. Tim to check how 
labour costs are used in the 
model and possibly ask LE to 
add them to define 
assumptions. Provide 
intermediate outputs, link to 
description of cost calculation 
in report. SEE APPENDIX 4: 
FINANCIAL MODELLING OF THE 
TECHNICAL REPORT 

 
  
  
 
 
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

How about this: 

These inputs specify the effect on total waste 
generation that is likely to occur when new 
garden, food and PAYT collection systems are 
rolled out to householders. For each new 
household on the system the amount of waste 
generation will change according to these 
figures. Where the figures are negative this 
represents a waste prevention effect, i.e. food 
waste generation decreases. Where positive, as 
for garden waste, generation increases at this 
rate. The total effect is calculated in the model 
by multiplying the per household factor given 
here by the total number of households. 

This text has been added to the "define 
assumptions" sheet. LE 17/02/2015 
It depends on the country selected. For some 
countries they are still heavily dependent on 
coal. For some countries no information on the 
marginal mix was gathered so the current 
average was used in the absence of other 
information. Agreed for all countries this would 
look odd. TE 16/02/2015 
I think we fixed this already. Mark will check 
and confirm. TE 06/01/2015 This is fixed, and 
BAU projections cannot be deleted MC 
09/01/2015 

Complete 

In “Define assumptions”, I still find the definition of 
“Waste Prevention Effects, kg per household” 
unclear.  

The default assumption for Electricity Grid Mix is 
100 % coal – is this credible? 

A projection can be deleted (or overwrite an 
existing projection) without warning or request for 
confirmation. This is especially a concern for the 
BAU projections. 

28/05/2015 

23 

 
 
 
  
  
  
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

Added in a change to make the 
banner red and Admin Mode 
appear in the top left of the 
screen. This should make it 
very clear when in admin / 
user mode etc. 

ok, will check this out, suspect part of issue 
might be in admin mode. We could change the 
header to a different colour to denote admin 
mode or something, to make it very clear. The 
row / column bars disappear in user mode to 
this is the easiest way to know. TE 16/02/2015 
The baseline scenario 1 is not editable in user 
mode, so I suspect user was in admin mode.  
But I have added the check to the macro to let 
you know you cannot 'save' baseline 1, and 
there was a bug in the save projection macro 
which is now fixed. A better way of noting 
admin mode (with a big 'caution' note) to be 
decided upon MC 18/02/2015 

The waste prevention targets tool is completely 
stand alone, it is for testing the effect of 
different initiatives measured against a set 
target only and does not affect the results of 
the main model runs. The setup waste 
prevention sheet does affect the model results. 
We'll add some clarification. TE 06/01/2015 MC 
to add guidance MC 09/01/2015 

When saving a projection, I got the following error 
message. I should add that I had loaded the 
Baseline 1 scenario, and that I had modified it – so 
this is maybe the reason – however, if I am not 
allowed to change this scenario, I would expect the 
error message to appear when I introduce the 
error, not when I save it. Moreover, I also get an 
error message when I try to save it as a new 
projection. I could still mark the step as “checked” 
(screenshot 19 and 20) 

The link between the “waste prevention targets” 
and the “waste prevention “ initiatives is not 
always clear. If one sets a “waste prevention 
target” in the sheet “Waste Prevention Targets”, 
does this affect the behaviour of the model? Or 
does this parameter only exist to verify whether 
the proposed measures are sufficient to reach the 
target? In the sheet “Waste Prevention Targets’, it 
is possible to set “Waste prevention initiatives”, 
but what if they conflict with those set in “Set Up 
Waste Prevention”? We have tried conflicting 
values, and have not received any notification of 
an error or even a warning. However, we do get 
the following error message when trying to update 
the graph: 

Screenshot 6 

 
  
 
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

bold / highlight added to text 
boxes on waste prevention 
setup /targets sheets. 

For the waste prevention initiatives, how can we 
be sure there is no redundancy with existing 
initiatives in some scenarios?  

For “home composting”, the link to “Average 
garden waste arisings per household”, “Average 
paper waste arisings” and “Total household waste 
arisings” has not been created yet.  

In this case, it seems particularly important to 
require the user to document user defined 
assumptions in detail. 

we can't it is very difficult to do this. Modelling 
waste prevention initiatives is a guess at best, 
we do make it clear that the initiatives are not 
existing programmes, but if you think this 
needs to come across more clearly let us know. 
TE 06/01/2015 

will correct this TE 06/01/2015 A link to the 
correct value has now been created. LE 
19/01/2015 

there is no real default to these numbers as we 
make clear. It is up to the user to confirm the 
numbers and adjust them based upon their 
own information. So the sheet itself is the 
record of the assumptions that were used. I'll 
check to make sure these assumptions are also 
recorded for each model run, and we'll add a 
free text field, as above, for users to add 
references to online documents or chapter 
numbers in accompanying reference 
documents. TE 06/01/2015 A free text field has 
now been added for the user to document the 
source. LE 19/01/2015 

All WP assumptions and sources are stored in 
the results file alongside each results run. TE 
16/02/2015 

These assumption should 
then also be shown in the 
results sheet as assumptions. 

28/05/2015 

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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

We do not find the labels and command 
descriptions very helpful. They are too long, they 
do not help the user to understand what he is 
supposed to do, and continuous reference to the 
UK case do not make, in our opinion, sense here. 
How representative are the UK studies for other 
member states? We refer, for instance, to this 
guideline here: 

“Analysis of UK case studies indicates an upper 
range of 270kg and a lower range of 97kg for waste 
prevented  per household  per year for this 
initiative. This range will obviously vary across 
Member States and should be adjusted  to reflect 
the conditions within the country being modelled. 
To help with this the average garden waste arisings 
across the whole country is presented in cell H26 
(this may vary from one region of the country to 
another depending on climatic factors and current 
service provisions).” 
Some minor issues: 

• In guidance note 1: “It is important to note that 
you you have to  define…” 
• .Guidance note 2: … average amount of garden 
waste arisings across the whole country is 
presented in cell H26….   We cannot see the cell 
numbers in the normal view 
• Average paper waste arisings/country – the 
amount is missing 
The Set up waste prevention tab is too long and 
therefore confusing. Is it possible, that when you 
choose the waste prevention initiatives from the 
first table, only those initiatives will be visible to 

The data is very poor, the UK data is all that is 
available. The instruction to users is that this 
tool provides a framework for calculating WP 
impacts but that they need to research their 
own values to be confident in them or just use 
the tool to test the impact by changing the 
values in different scenarios. We really can't do 
much more here, but we will make it clearer 
what is expected from the user, and if they 
can't find a method to be confident in 
assumptions for a particular initiative they 
shouldn't use it. TE 06/01/2015 

Our WP tool has been fine for Welsh 
Government and is well used in the UK. 30 
working days additional seems pretty 
significant. We have delivered a WP tool as per 
the contract so we are not expecting to do any 
more work on this element of the model. TE 
16/02/2015 

ok, will address these issues TE 06/01/2015. 
These issues have been addressed. LE 
19/01/2015 

Ok makes sense TE 06/01/2015. Done - only 
waste prevention initiatives selected in the first 
table are now visible to the user. LE 
19/01/2015 

The ETC waste prevention 
expert has done a first 
analysis of the measures and 
identified additional data 
sources. He suggested some 
improvements of the module 
with an estimated resource 
need of 30 working days. We 
need to discuss how to 
further proceed. 

Almut to send list of initiatives 

macro check boxes that hide 
unhide rows 

 
 
 
 
  
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

the user? 

“Percentage of households that are likely to act 
after seeing/hearing advertisements”: is that 
percentage calculated compared to the total 
population or compared to the number of 
households seeing the ads? 

It is possible for the user to ask for a Sensitivity to 
be deleted (or to overwrite an existing projection) 
without warning or request for confirmation.  

However, when we tried to create a new sensitivity 
analysis, we were not able to cancel it. Thus, 
apparently the button “delete sensitivity Set” 
(restore default) is not working. 
By mistake we wrote some text in the central value 
of some material revenues (see below). The system 
allowed us to save it (pressing the “save 
sensitivity” button) without warning (we do not 
know the consequence of it in trying to run a 
scenario).  

Screenshot 7 

However, if we save it as a new sensitivity the 
below message appeared:  

Screenshot 8 

Will check with Thomas (model author) when 
he is back from paternity leave and clarify. TE 
06/01/2015 
the percentage of households likely to react 
after seeing/hearing advertisements is the % of 
those likely to see/hear the advertisements, 
not of total population. clarification added to 
WP sheet 08/03/2015 

this should be addressed now with warnings 
etc, but Mark can you check. TE 06/01/2015 
Checked and added request for confirmation 
MC 07/01/2015 

We are adding data validation rules to all 
numerical inputs cells so that text values 
cannot be added by mistake. TE 06/01/2015 

There are still some unanswered questions in the 
“comments” “that you have posted yourselves.  

thanks, yes we will address these. TE 
06/01/2015 

28/05/2015 

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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

When we load a new “Policy Scenario”, the 
contents of the cell “Scenario name” sometimes 
remain the same (whether or not this happens 
appears to depend on variables that we do not 
observe). Is this “scenario name” then a variable 
that is only used internally in this sheet, and that is 
not saved?  
The contents of the sheet does not always change 
when I change the option from the dropdown 
menu from “set landfill reduction” to “Set residual 
treatment split”. Sometimes it does, sometimes it 
doesn’t. Does this reaction depend on the 
fulfilment of some external condition.  
We have been able to change the “Latest data 
year”, “Target year” and the “Rate” for the Waste 
Framework Directive without any warning or error 
message. Same for the “Landfill Directive “ target.  
For instance: 

Screenshot 9 

Are the landfill directive target years right for all 
the countries, e.g for Finland and the Netherlands 
the target year in the tab is 2020? 

A policy scenario can be deleted (or overwrite an 
existing projection) without warning or request for 
confirmation. 
It is not clear what the model will do exactly if one 
chooses not to meet the targets of the Waste 
Framework Directive. How will recycling, 
incineration rates etc evolve? Will they be set 
equal to those of one of the baseline scenarios?  

Mark to check. TE 06/01/2015 Working fine - 
can't think of reason for error MC 07/01/2015 

no it shouldn't do, mark to check. Otherwise 
we'll need to do a web conference so we can 
see your model working on your system. TE 
06/01/2015 This is a simple show/hide macro 
so will need to check on your system MC 
07/01/2015 

yes as above this is because the cell locking 
function wasn't enabled in the version we sent 
you, this is now sorted. TE 06/01/2015 

I believe so, Mark to check the table. I would 
imagine FI and NL are before 2020. TE 
06/01/2015 Table in C&O had wrong croatia 
position in. Corrected MC 15/01/2015 

I think this is sorted, Mark to check TE 
06/01/2015 Added in 07/01/2015 

Yes the baseline rates are used instead. Mark to 
add some guideance on process etc. TE 
06/01/2015 

If you set that you want to meet the targets of the 
Landfill Directive, but do not specify the method 

the baseline shares are used . Mark to add 
some guidance on process etc. TE 06/01/2015 

seems ok now 

 
  
  
  
 
  
  
  
  
  
  
  
  
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

for residual treatment, what assumptions are then 
made with respect to this variable? 

When we set some values for additional recycling 
targets, we sometimes get the feedback that our 
values are not valid. We suppose this is to prevent 
the user from introducing absurd values, but the 
error message is not informative on what is 
precisely wrong with our input. Note that we got 
the following error message when we introduced 
“60” “out of the blue”: 

Screenshot 10 

However, when we gradually increased my input 
for the recycling% in 2024(say, first 51%, then 52%, 
etc, ), the error message disappeared: 

Screenshot 11 
It is possible to modify the top rows in MBT 
Treatment Split without error message: 

Screenshot 12 

What is the meaning of the rows with “model 
controls” on the bottom of the sheet?  

Concerning the text box “To compare this policy 
option under different assumption sets save this 
scenario, then change the assumption set and click 
'Save as New Scenario': to reduce the risk of error, 
could a function be added that adds to the name of 
the scenario whether or not the user defined 
assumptions have been used? Same remark applies 
to the “Waste prevention scenarios”. 

The restriction is set to only input numbers as 
percentages from 0% to 80%. We will make a 
note of what the restriction is for clarity. TE 
06/01/2015 Added note MC 07/01/2015 

yes as above this is because the cell locking 
function wasn't enabled in the version we sent 
you, this is now sorted. TE 06/01/2015 

These are hidden model controls for admin 
users only and will be hidden for the version 
sent to users. TE 06/01/2015 
The drop-down box will show the assumption 
set chosen for each saved policy scenario, so if 
it was saved with UD assumptions it will clearly 
indicate this  and in the assumptions data saved 
with model results, so I suggest not to make 
any change to the scenario name, this would 
make the name look a little cumbersome. TE 
06/01/2015 

28/05/2015 

29 

 
 
 
 
  
  
 
  
  
  
  
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

This is the year from which the policy starts to 
take effect and from date the trajectory from 
baseline to target rate is set. Mark will add 
some clarification to describe how this process 
and the goal seeks work. TE 06/01/2015 

Edit text for clarity and make sure explained in 
more detail within the guidance - MC 

What is the meaning of “the year in which the 
ban/target reduction will be announced in”?  

1. The following textbox is not clear to me: 

How the Model Works: Residual Treatment 
If you set a landfill reduction target, this will not 
change the recycling collected rate.  Instead, the 
model will divert enough waste from landfill into 
MBT or Incineration to meet the target. 
It will start this diversion from the ‘year 
announced’ and linearly change the percentages of 
residual waste going initially to landfill, MBT and 
Incineration, so that the targets are met in the 
target year. 
How does the model choose between MBT and 
Incineration? 
It assumes that in the target year, the ratio of 
MBT:Incineration will be the same as the ratio 
would be without the target.   
However, if (normally due to low recycling rates 
and high MBT use) the final landfill rate still does 
not hit the target, then all residual waste is 
assumed to be incinerated in order to meet the 
target landfill reduction. 

The second sentence seems to imply that the sum 
of waste diverted to MBT or incineration will be 
sufficient to meet the landfill reduction target. 
However, according to the last sentence, it is still 
possible that this procedure does not result in 
automatic compliance with the target. 

 
  
  
 
 
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

It seems like there is a duplication in boxes 
(screenshot 21) 

It looks like there are missing values hen applying 
the residual treatment split (screenshot 22) 

The user is not required to document the splits he 
proposes for residual treatment, MBT treatment 
split and incineration split.  

It is possible to modify values in the “Hidden 
scenario controls” without error or warning 
message. It is not completely clear what the 
meaning of these cells is, but should they not be 
hidden unless they reveal an error or should lead 
to a warning? 
It is still possible to ask the model to run with 
“EU28” as the selected country. This leads to the 
following error message: 

Screenshot 13 
Using the Waste Prevention Targets Tool leads to 
the following error message: 

Screenshot 14 
When I force all scenarios to use the default 
assumption set, this is not reflected in the table 
with the scenarios. The same happens when I 
impose the “user defined” scenario (Screenshot 23 
and 24) 
When I run the model, I get the following error 
message: (Screenshot 25). I then get the following 
results (Screenshot 26) 

ok, will take out. TE 16/02/2015 This is now 
taken out LE 17/02/2015 
mark to check values coming in from datastore 
correctly and baseline values linking to correct 
cells - MC Fixed (apart from current year ref 
errors) MC 19/02/2015 
These are model inputs. The user shouldn't be 
required to justify the choice of every model 
control in the model. That would be very 
unwieldy. That is what accompanying technical 
reports are for. TE 16/02/2015 

I think we just left them unhidden so you could 
see them when carrying out the review, they 
will be hidden for the version sent to users. TE 
06/01/2015 

this is now sorted. TE 06/01/2015 

Mark check this error is now resolved. TE 
06/01/2015 Done  MC 07/01/2015 

ok good point. TE 16/02/2015 yes can revise - 
MC Fixed MC 19/02/2015 

fixed TE 16/02/2015 

28/05/2015 

31 

 
  
  
  
  
  
  
  
  
 
  
  
 
  
  
  
  
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

It is still possible to mark steps as “checked” 
without first checking the previous steps; However, 
the user gets a warning when he tries to run the 
model without completing all steps.  I think this is 
sufficient.  

Why give the option to show the results for the 
“EU28” if scenarios are run per country? Maybe 
modify “Results for individual countries or the EU 
as a whole can be selected.” accordingly.  

In “final destination”, what is the meaning of 
“mass loss”? 

In the GHG impacts, what is the meaning of 
“avoided emissions”? We understand that this is, 
compared to the “baseline to run scenarios 
against”? Same question concerning costs and 
benefits.  

Saving the results is not done automatically, but 
requires the user to click on “Export results”, which 
is somewhat hidden down in the sheet. Should the 
user not be asked to save the results whenever he 
tries to close the workbook, when he runs a new 
scenario, changes assumptions, changes the 
country etc?  

It would be over burdensome to have a very 
strict procedure to control the model. One 
might want to do some work at one point in 
time and another later on. The model makes 
sure the user is made aware that not all steps 
are checked when they try to run the model. 
This seems perfectly adequate. TE 16/02/2015 

The EU-28 results are most important output of 
the model for EEA / commission, so I think the 
heading / function is fine. TE 06/01/2015 

OK, we have no further 
comments. 

Mass loss is evaporation from MBT processes 
that needs to be taken into account to get mass 
balances through the model and in the overall 
results. Will add a clarification here. TE 
06/01/2015 Text box added to model to clarify 
this. LE 19/01/2015 
Avoided emissions are emissions that are 
avoided from transferring the production of 
energy from grid to the EfW plant. Not 
compared to baseline, this is controlled by 
comparing one scenario against another. Will 
add a clarification in case the user is unfamiliar 
with the technical appendix where it is set out 
in detail. TE 06/01/2015 Clarification added. LE 
19/01/2015 
Agreed, we propose to change the functionality 
so the control and outputs file is used to setup 
and run the model only. The results will be 
automatically moved to a separate file and 
saved, along with any user defined 
assumptions, each time the run model button is 
pressed. TE 06/01/2015 

text boxes for this and ones 
below] 

 
  
  
  
  
  
  
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

It is a bit of an issue of sound 
file management to separate 
input files, calculations files 
and out files in separate 
folders. 

The model saves the files in the 
same folder. It is up to the user 
what they do with them 
thereafter, and something that 
can't be controlled through 
Excel in any case. TE 
05/03/2015 

OK, we have no further 
comments. 

Would it be possible to allow the user to save the 
results in a different folder as the folder with the 
calculations workbooks?  

The results file is identified by date and time of 
creation, but is still possible afterwards to modify 
parameter such as for instance the country for 
which the results are displayed. How can we verify 
which input parameters have been used?  

How is it possible to have zero share for “final 
destination” for all possible destination? See table: 

Screenshot 15 

It may be a matter of taste, but we find it a bit 
confusing to allow the user to choose for the 
display of “relative scenarios” and “relative from 
2011”, while there are already separate sheets 
representing these results.  

The control and outputs and calculations files 
must be in the same folder. Once the results 
file is saved the user can move it wherever. Is 
this clear enough or is clarification required? TE 
06/01/2015 

Even if the user was stopped from saving the 
file if a different file, they could just move it 
with windows explorer. Something we have no 
control over. As far as I'm concerned good file 
management is not in scope of the functionality 
of this model. TE 16/02/2015 
The only thing we can do is lock the cells and 
protect the file. We will do this, but if you have 
any further suggestions, let me know. TE 
06/01/2015 Cells have now been locked in 
results overview sheet. LE 19/01/2015 
This was because you had the EU28 selected 
and we had not completed an additional 
calculation that was required to generate this % 
in this view, it works by country. We will 
complete this calculation for the final version. 
TE 06/01/2015 

The background sheets are calculation ones 
only and will be hidden. TE 06/01/2015 

28/05/2015 

33 

 
 
  
  
  
  
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

no it is up to the user whether the results are 
absolutes or compared to a baseline. This is set 
with the controls in sections 1 and 2 of the 
Results Overview sheet. TE 06/01/2015 

Yes, it is a control at the top of the sheet. We 
have also added the scenario and baseline (if 
applicable) names to the chart headers. TE 
16/02/2015 

Is it visible in the results 
sheets which option has been 
chosen?  

This change has now been implemented, but 
the MS / EEA versions still need to be set. TE 
06/01/2015 Still need to fix results country if 
not in EU mode, and confim hidden status of 
other results MC 07/01/2015 Incorporated into 
results change - countries to only access their 
own results by removing data validation on 
country select button prior to exporting results 

“Tables with key results are displayed on this 
page”: maybe modify to “Tables with key results 
compared to the chosen baseline scenario are 
displayed on this page”. 

In a previous mail, we had raised the following 
question: 

The sheets “Scenario *** results” show the 
absolute results of each independent scenario. On 
top of the sheet, one can find the results for the 
most recent country for which the model was run. 
Further down the sheet, one can find the results 
for all other countries for which the model has 
been run. Are these in alphabetical order? Can we 
be sure that “scenario ***” means the same for all 
countries in the sheet? As far as I understand it, 
this sheet contains the result for the scenario that 
is called “scenario ***” in the model for this 
country, but the actual scenarios that fall under 
this name may vary from country to country. 

You had then answered: 

At the moment, scenario 5 (for instance) can be 
different for each different country, and the name 
at the top of the scenario 5 sheet is the name of 
the scenario in the country that the controls sheet 
is currently editing.  So the EU-28 results, for 
instance, will be misleading unless all countries 

 
 
  
 
 
 
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

have the same scenario for scenario 5.   
However, the user interface for this sheet will be 
altered slightly: 
A single country will only be able to see their own 
results named under the scenario names they have 
created.  They will not be able to see the other 
countries or the EU-28 results, so this will not 
matter.   
To run the whole EU-28, we will have a ‘short-cut’ 
way, so that you don’t need to set them up for 
each country independently.  You will be able to 
set up 10 scenarios which will be used across all 
countries, so the results will be comparable: and 
the sheet will pick up the correct scenario names. 

Is it possible that this change has not been 
implemented yet?  
We have exported the results and the system 
generated a new excel file named 
“EuRM_MSWM_Results” , which at the bottom line 
of the result overview pages allowed  us to export 
the results again. This option is useless and 
probably misleading.  

The result section do not include enough 
information on the model settings used to 
generate the obtained results, and this raises a 
replicability issue. It would be very useful, if 
possible, to have among results a tab about the 
settings, i.e. characteristics of different scenarios, 
data source used for the sensitivity analysis etc. 
The more information available the better. 

Yes, I couldn't work out in short time how to 
delete the button with the macro. This will now 
be irrelevant as we'll automatically export the 
results after each model run. TE 06/01/2015 

Ok, the data is now stored in the background 
files, but we haven't pulled this through to the 
results overview sheet yet, we will add as much 
information as we can. TE 06/01/2015 

Get formatting and row 
headings from "Direct Inputs" 
sheet in calculations file and 
put this into the "Scenario 
Results" sheet in the 
unformatted data between 
results. 

Get rid of export results bit in 
results overview.  

28/05/2015 

35 

 
 
  
  
  
 
 
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

New sheet called "assumptions 
overview". Import the correct 
assumptions (using format 
from direct inputs sheet) for 
each scenario/country for that 
particular model run. Set these 
cells to blank if scenarios are 
relative. (put in an note saying 
that you can't combine 
assumptions). 

Add new sheet to export 
results macro. 

When the run is completed, Excel automatically 
opens certain sheets, wouldn’t it be better to open 
the Results Overview –sheet, and to give options to 
the user which sheets he wants to open?  

In the result graphs, there is no title (e.g. which 
country). 

Finish collections summary output sheet - fuel 

Yes we didn't set a sheet at the end of the 
macro. We'll just take the user back to the run 
model sheet as the results will be moved to a 
separate file. TE 06/01/2015 Incorporated into 
results export change MC 09/01/2015 
We will add a dynamic name to the chart, 
country + scenario etc. TE 06/01/2015 A 
dynamic name (Country - Scenario) has been 
added to the charts. LE 19/01/2015 
Tim - you were planning to look at fuel 
consumption. Also we were going to think 
more about the calculation for waste through 
transfer stations and dry recycling sorting 
plants. The rest of the sheet is finished but 
would be worth reviewing it quickly. LE 
17/02/2015 

Fuel consumption is almost sorted - need to 
work out how to calculate the number pf 
households covered by system type for latest 
year. also get Tim to review what I've done 

 
 
  
  
  
  
 
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

In the Controls and Outputs file, I set up a user 
input in the “Define Assumptions” sheet. The user 
can select the price year for the costs in the model 
(please check wording/layout of this new section in 
the “Define Assumptions” sheet) 

Sort out remaining external links. • Data validation 
to sort out external links 
o Test if moving sheets to another workbook 
messes up data validation, if so Chat to Tim 

Cells AG142:AH142 in the “Collections 
Assumptions” sheet, Calculations file – not sure 
what is going on here could you take a look? 
Research the scope of named ranges and how we 
can merge them 
• Look at data that is pulled through from the 
assumptions data store and make sure that when 
you have the same data being pulled through for 
every country either: 
o Fix it properly 
o Or blank out in calculations file the cells that are 
not for the current country 
• Collections Summary Outputs 
o Do same for target year 1 2 and 3 for waste 
through transfer stations        
o Household on key services, first table for 2020 
cell to right of sheet just use same formula but for 
target year 0 
o Next table – pull data straight from waste 
prevention effects sheet no interpolation necessary 
delete redundant tables 
Each hidden sheet in Controls and Outputs should 
have a description for each page and table 

already for fuel use. 

 Completed. 

All sorted now LE 21/02/2015 

Went through and re-did data validation but 
still cannot delete external links - what to do? 
LE 24/02/2015 

refs broken, now fixed 

 Completed. 

Cells have been blanked out in calculations file 
for countries other than the current country. LE 
16/02/2015 

Completed. 

Completed. 

28/05/2015 

37 

 
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

• Set up Waste Prevention – box to side that 
provides reference UK price. And hard code input 
box to this price 
o Adjust formulas so that price level indices are 
applied first to 2012 prices and then they are 
inflated to current year prices 
Finish goalseek macro 
Reinstate opening/closing the calculations file 
when a new country is selected 
Set up Waste Prevention sheet. Need to check 
"Proportion of households receiving a NEW 
'reduced sized' residual waste bin in each year" 
and "Proportion of total housing stock covered by 
no side waste policy". These are hard coded but 
labelled as calculations? 
test annual update again 
Store copy - contains a lot of references to Old 
Calculations file (EuRM_MSWM_02 - Waste Flow 
Calculations) and also to a file called Targets.xlsx 
Make GDP deflators editable by user 
waste arisings projections sheet. Should we 
automatically enter data for full projections where 
we have it?  And also for 5-yearly projections 
should we enter year for 2015/2020 if we have it? 
Check how NPV calcs are done and adjust formulas 
in 8. Full Model Outputs sheet accordingly so data 
from the right range of years is picked up. Also 
check NPV formulas in "Relative from 2011" sheet 

Rows 42:56 SUPS. Cell G50 check what comes in 
here. Cells H to J 50 data validation? 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Data validation 20% to 80%. Collection for 
recycling % is sum of collection for recycling 
and collection for biowaste from actual data. 

yes automatically enter data 

 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

Chat about making sure that the material 
composition projections match the waste types 
inputted in annual data - perhaps when inputting 
manual data the user should be able to see the 
waste tonnages for each material from the last 
year of data in the mdoel 

Pull through information in column H of annual 
data, for recycling tonnages and treatment 
shares 

Look through all countries and where a 
particular material stream is not in use for a 
particular country. When we change a country 
we hide the rows in waste arisings projections 
and manual annual update 

Freezing panes – need to be redone when setting 
user and admin mode 

Completed. 

In annula update what happens to the overall rate 
if I set more than the rate by the sum of the 
material tonnages / total tonnage? 

look in historic data and check how collection 
for recycling and biowaste is calculated - put 
this in. Put in a specific data validation 
message. "You cannot enter rates such that the 
level of landfill falls below the level of 
uncollected rate which is calculated by 100% 
minus the collection rate below". No check at 
the end of the model. Get rid of check to 100%. 

Tim - look in historic data sheet, collection for 
recycling % has to come from the model if the 
recycling tonnages are inputted as Total. This is 
an issue for doing it this way! Can chat more to 
explain if necessary. Load into model then goal 
seek landfill, calculate RR as per historic data 
calcs, then show to user. 

UDA Paper and card rows need removing for 
material revs. Take out separate paper and card. 
Trace dependents first 

 Completed. 

UDA reject rates – bulk collection for bring? 

Progress meter for run sensitivities 

should not be a problem now the rates are 
being taken out 
wait until Mark 

UDA default source needed 

Completed. 

28/05/2015 

39 

 
 
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
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Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

needs to check upper/lower sensitivity analysis 
values - rej rates only 
Early warning outputs – add to results sheet 
if the user doesn’t set the collection coverage > 0 
then the model creates a div 0 error. We need to 
stop users being able to do this 
WP targets tool update graph button doesn’t seem 
to have any effect when less scenarios are chosen 
Need to make sure waste prevention financial 
costs are displayed in the results sheets. Also 
display private/social metrics financial costs in 
results sheet. Remember to change sum function 
from rows 14500 to 15000 in Scenario 1 results 
sheet. Sort out choose functions so they are 
displaying the correct figures. Also make sure that 
the results sheets display the correct real terms 
year in the titles. Check units of results compared 
to full model outputs. 
Notes for macros still visible in sensitivity analysis 
sheet 
Sensititivity Analysis - Document method for 
adding a new variable to the sensitivity analysis 
page 

Macros - Error messaging 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Done - need to correct adding to datastore 

• Find if there is a VBA function that completely 
exits macro running rather than just the sub 
• Check if its possible to get the errorcode 
when an error comes up and to concatenate 
that into the error message box 
o “Unfortunately an error has occured. Please 
save file and contact system administrator.” 

Waste Prevention - Insert checks and bounds 

Completed. 

 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

UI - create version of results for single country view  Completed. 

In collections module we use miles - should be km  

UI Assumptions - add collection cost per household 
as a user defined option. Or something similar. 
Can the model include open/closed loop recycling 
for glass. Speak to Tim. Eunomia to consider if this 
can accounted for.  
AUTO ZOOM TO FIXED RANGES ON SHEETS 
The collections module should take into account 
housing stock - e.g. the number of people living in 
high rise buildings. This should also feed into 
recycling rate as levels of recycling from these 
houses are likely to be lower. 
Put progress bar on open macro code 
Save as macro free workbook when sensitivies run 
– try to stop message box appearing – maybe fix as 
.xlsm 
Restore defaults sets plastis RR to no. Cell H35 in 
sensitivity analysis is reset to no sort this out? 
Check position of progress bar in annual update 
Hide calculated tonnage recycling composition 
tonnage as well – EDC 
Clear time/date stamps when changing country 
Drag across waste prevention calcs to 2035 in 
controls and calculations – check each one! 
AD inputs in datastore 
Check recycled table in results overview is it 2030, 
doesn’t seem to match up with table above 
Sensitivity Overview sheet - links in left hand 
column to analysis sheets don't work 

28/05/2015 

what measure to use km/L or 100L/km?? Not 
sure if this is really critical as calcs are hidden 

Not really possible, as too many permutations 
of collection systems 

Speak to Ann this can probably go in the list of 
things the topic centre could update 

low priority 

Completed. 

 Completed. 

 Completed. 

 Completed. 

 Completed. 

 Completed. 

 Completed. 

 Completed. 

 Completed. 

Completed. 

Completed. 

` 

41 

 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Comment 

Eunomia Reply 

Further response from Topic 
Centre 

Discussed at Meeting 17.02.15 

Sensitivity analysis sheets - block of colour next to 
links at right hand side of change doesn't change 
from sheet to sheet 
Is discount rate now sorted? Should the "4% in 
results overview be linked to something? 
Change chart buttons to hyperlinks and put in vba 
for results file only that unhides tabs at bottom of 
sheet. Take out back buttons on charts. 
hide EDC, manual and WAP material stream rows 
by composition not by recycling collected (from 
composition data store) 
Check the format of the results file (e.g. hiding tabs 
at bottom and columns at side etc) 
Reset all stored data in Controls and Outputs (for 
sensitivities, scenarios, projections etc) to default 
for all countries before sending out 
Check with Tim about saving sensitivities in 
national currency - do we need to change what is in 
store currently and have two different default 
options that load? 
Waste Prevention Targets graph - axis label? 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

Completed. 

 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
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doi:10.2779/871316