Municipal waste generation - outlook from OECD

Assessment versions

Published (reviewed and quality assured)

• No published assessments

 

Rationale

Justification for indicator selection

Since the use of resources and generation of waste accompany any economic and social activity, their environmental pressures are far-reaching and range from climate change and water pollution to soil degradation and loss of biodiversity.

Waste also represents an enormous loss of resources in the form of both materials and energy. The amount of waste produced can be seen as an indicator of how efficient we are as a society, particularly in relation to our use of natural resources and waste treatment operations.

Municipal waste is currently the best indicator available for describing the general development of waste generation and treatment in European countries. This is because most of the countries on Pan-European region collect data on municipal waste; data coverage for other wastes, for example total waste or household waste, is more limited.

Municipal waste constitutes only around 15 % of total waste generated in the EU-25, but because of its complex character and its distribution among many waste generators, environmentally sound management of this waste is complicated. Municipal waste contains many materials for which recycling is environmentally beneficial.

Despite its limited share of total waste generation, the political focus on municipal waste is very high.

The main purpose is to provide a measure of the environmental pressure of the generated municipal waste. In general, the waste intensity represents a driving force indicator and shows response of the society to raise the eco-efficiency of human activities.Municipal waste generated per unit of GDP (waste intensity) will show if there has been any decoupling of waste generation from economic growth. Municipal waste generation per capita allows comparisons of countries.

The outlook presents plausible future of municipal waste generation in some countries of Pan-European region and can be used for estimation of its impact on environment (particularly when it comes to contribution to land-use and GHG emissions). It helps to assess achievability of targets and identify appropriate policy response options for making consumption patterns more sustainable.

Scientific references

• EEA Core set of indicators (CSI)
• Generation of Industrial and Municipal Solid Waste UNSCD 2001
• EECCA core set The core set is based on the 'UNECE Revised guidelines for the application of environmental indicators in Eastern Europe, Caucasus and Central Asia'. Guidelines are developed within the framework of the "ENVIRONMENT FOR EUROPE" PROCESS by the Working Group on Environmental Monitoring and Assessment.

Indicator definition

Definition: The indicator presents the outlook of total amount of generated municipal waste per year by regions: Central and Easter Europe, Western Europe and non-OECD countries. The total % change from 1995 to 2020 allows to compare regional performance.

Model used: JOBS, POLESTAR

Ownership: Organisation for Economic Cooperation and Development

Temporal coverage: 1995, 2010 and 2020

Geographical coverage: Austrlia&New Zealand, Canada, Mexico&USA, Central and Eastern Europe, Japan&Korea, Western Europe Central and Eastern Europe -Czech Rep, Hungary, Poland, Slovak Republic, Turkey, Romania, Bulgaria; Western Europe - Austria, Belgium, Cyprus, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxemburg, Malta, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom
global

Units

Million metric tons per year

Total % change

 

Policy context and targets

Context description

Global and Pan-European policy context
No international agreements exist for reduction in solid waste production.  

EU policy context

6th Community Environment Action Programme

• Better resource efficiency and resource and waste management to bring about more sustainable production and consumption patterns, thereby decoupling the use of resources and the generation of waste from the rate of economic growth and aiming to ensure that the consumption of renewable and non-renewable resources does not exceed the carrying capacity of the environment.
• Achieving a significant overall reduction in the volumes of waste generated through waste prevention initiatives, better resource efficiency and a shift towards more sustainable production and consumption patterns
• A significant reduction in the quantity of waste going to disposal and the volumes of hazardous waste produced while avoiding an increase of emissions to air, water and soil;
• Encouraging reuse, and for wastes that are still generated: Preference should be given to recovery and especially to recycling.

EU waste strategy (Council Resolution of 7 May 1990 on waste policy)

•  Where the production of waste is unavoidable, recycling and reuse of waste should be encourage

Communication from the Commission on the review of the Community strategy for waste management (COM(96) 399)

• There is a considerable potential for reducing and recovering municipal waste in a more sustainable fashion for which new targets also will be set.
  

• There is a considerable potential for reducing and recovering municipal waste in a more sustainable fashion for which new targets also will be set.

The European Neighborhood Policy, STRATEGY PAPER

• Priorities will be identified in key areas such as water quality, waste management, air pollution and the fight against desertification.

EECCA policy context

EECCA Environmental Stretegy

• Development of inter-sector waste management action plans
• National capacity building for the environmentally sound management of hazardous waste
• Implementation of integrated systems of monitoring of waste transfers
• Development of economic mechanisms to facilitate implementation of cleaner technologies and waste prevention and minimization as well as governmental support for waste treatment facilities
• Development of efficient programs for waste management and management of chemical risks
• Promotion of development of an integrated system for inventory of waste generation and accumulation (e.g. Protocol on Pollutant Release and Transfer Registers-PRTR)

EECCA Environmental Strategy

Targets

EU level

Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste

• By 2006, Member States are restricted to landfilling a maximum of 75% of the total amount by weight of BMW produced in 1995. This target increases to 50 % in 2009 and 35% in 2016.
• Countries that landfilled more than 80 % of BMW produced in 1995 may postpone the attainment of these targets for a maximum of four years.
  

The 5th EU EAP had a target of 300 kg household waste per capita, but no new targets have been set in the 6th EAP because of very low success with the 300 kg target, which is therefore not relevant for further use.

EECCA level

Some countries have set national targets for the reduction of solid waste within a specified time frame however these targets are not reported at the international level. Special research is needed to identify availability of targets at the EECCA countries.    

Related policy documents

• Directive 99/31/EC on landfill of Waste
  Directive 99/31/EC on landfill of Waste
• Sixth Environment Action Programme (decision No 1600/2002/EC)
  DECISION No 1600/2002/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 22 July 2002 laying down the Sixth Community Environment Action Programme

 

Methodology

Methodology for indicator calculation

The projections of municipal waste generation to 2020 are calculated using an OECD global, dynamic equilibrium model (JOBS) in combinations with Stockholm Environmental Institute's PoleStar framework.

The total % change from 1995 to 2020 are calculated based on the historical data given in OECD Environmental Data Compendiums published by OECD in 1997 and 1999 and in the report Doorn M.R.J and M.A. Barlaz (1995) 'Estimate of Global Methane Emissions from landfills and Open Dumps' EPA 600/R-95-019 and results of the PoleStar framework. (see also Key Model Assumptions for the Reference Case).

Overview of the Models

JOBS model

JOBS is a neo-classical equilibrium model that was initially constructed to asses economic impact of globalization on individual regions of the world. JOBS is a version of LINKAGE model, used in OECD Linkages II project. The LINKAGE model was in turn derived from GREEN model that was used in series of analyses of policies to combat the Climate Change.

JOBS is designed for the analysis of dynamic scenarios, which are solved as a sequence of a static equilibria.  The time periods are linked by exogenous population and labour supply growth, capital accumulation and productivity developments. The JOBS model is implemented with GAMS software, and includes flexible aggregation facility which may be set up to 50 sectors and 45 regions. For the OECD Environmental outlook it covers 26 sectors and 12 regions.

Sectors: rice, other crops, fisheries, livestock, forestry, minerals, coal, crude oil, natural gas extraction, petroleum and oil products, gas manufacture and distribution, electricity generation and distribution, meat from all types of animals, other food, chemicals, iron and steel, non-ferrous metals, wood products, pulp and paper publishing, motor vehicle manufacturing, other manufacturing, construction, water supply, trade and transport services, services, dwellings.

Regions: Western Europe, Central and Eastern Europe, Former Soviet Union (For definitions see page 315 at the OECD Environmental outlook 2001)

The production structure used in JOBs is presented at the Fugure A1 of OECD Environmental outlook 2001, page 316. Input of the model - non-energy intermediate inputs, energy intermediate inputs, one category of labour, one type of capital and a natural resource factors used for the Forestry, Fisheries, Minerals, Coal, Natural Gas and Crude Oil Sectors.

Demand, production and prices in all sectors and regions are determined simultaneously in JOBS. The assumed household income elasticities are among the important "drivers" of the model. They reflect how much household demand for a given category of products will change when incomes change. The assumed substitution elasticities between various production factors are also important in determining simulation results. These elasticties tell how much the composition of factors use will change when the relative price between factors alters. 

The results from the JOBS model are fed into PoleStar framework with macroeconomic variables setting the scale of activities within the sectoral modules. Once the economic and demographic parameters have been entered, projections for environmental and resource pressured are developed.

PoleStar framework

Polestar is an accounting framework for combining economic, resource and environmental information to examine alternative development scenarios. The model algorithms and scenarios rely on an update on the Global Scenario Group's Bending the Curve scenarios  (Raskin, et all., 1998; Heaps, et all., 1998)
The PoleStar System is applicable at national, regional and global scales. It allows customizing data structures, time horizons, and spatial boundaries - all of which can be changed in the course of an analysis. PoleStar is not a rigid model and it accepts information generated from formal models, from existing studies, or any other sources.  PoleStar comes with an initial framework, the Basic Structure, which was modified so that the results from JOBS simulations could be used as drivers for environmental impacts simulated in the framework.
Polestar covers a number of issues including: energy, water resources, raw materials, agriculture, land use, solid waste generation and management, environmental loadings, income distribution and poverty.
More information about the Polestar Framework can be found here.

Key model assumptions for the reference case

The base year data used in JOBS model were mostly taken from GTAP (Global Trade Analysis Project, Version 4) data base developed by Purdue University with 1995 as a base year. In addition to the base year data, assumptions are made in the Reference Scenario concerning:
- total GDP developments (based on OECD Economic Developments projections);
- population growth (based on UN median fertility estimations);
- labor supply (based on OECD Economic Developments projections and UN population data );
- supply and productivity of curtain agricultural inputs (based on OECD Agricultural Directorate analysis).

The assumptions on the assumed household income elasticities can be found in Annex 2 of the OECD Environmental outlook, 2001 (p.314).

The Reference Scenario is based on Current activities and trends. It does not take into account the adoption or implementation of new policies.

In the base year, waste generation rates in OECD regions, are based on data given in OECD Environmental Data Compendiums published by OECD in 1997 and 1999. In the remaining regions, waste generation rates in rural and urban areas are based on the default regional generation rates given in the report by Doorn M.R.J and M.A. Barlaz (1995) 'Estimate of Global Methane Emissions from landfills and Open Dumps' EPA 600/R-95-019 prepared for US Environmental Protection Agency Office of Research and Development. In the scenario, high-income OECD (including Europe) generation rates are, in accordance with developments over the last decade, assumed to increase at a slightly lower rate than GDP, while other regions converge toward the average rate in high-income OECD regions as income increase.  

For more information see OECD environmental outlook (2001) Annex 2 p.323.

Methodology for gap filling

The base year input data on waste generation in non-OECD countries come from Doorn M.R.J and M.A. Barlaz. For most countries, data on total waste in place are not available and had to be developed from waste generation rates. The total annual waste generation rate (Tg/yr) is obtained by multiplying Municipal waste generagtion rates with population data.  Per capita MSW generation rates range from 1.7 to 1.9 kg/day for the U.S. and Canada. Per capita MSW generation rates in other developed countries are about 1.2 kg/day (also for Europe?). For developing countries, rates are about 0.8 kg/day for urban, and 0.3 kg/day for rural areas. Substantial uncertainty in the global estimates from this source results from a lack of data characterizing (1) country-specific waste generation, (2) waste management practices.

Methodology references

• OECD Environmental Outlook Description of the models and assumptions to the reference case are presented in the Annex 2 p. 313.
• PoleStar framework History, description of the model, software, publications, links.

 

Data specifications

EEA data references

• No datasets have been specified here.

External data references

• Input data to PoleStar model - Waste generation rates in OECD regions
• Input data - waste generation rates in other regions
• Outlook - Municipal waste generation from PoleStar model
• Input data to the PoleStar model from the JOBS model - ecomomic development, GDP, level of urbanisation, etc.
• Input data to JOBS model for economic projection, GDP, etc.

Data sources in latest figures

 

Uncertainties

Methodology uncertainty

Uncertainties related to the models

Some selected limitations of the JOBs model

The model does not include the investment function which relates the overall level of investment to the expected rate of return. There is no forward looking investment behavior incorporate in the model. Instead the value of investments in each year and region is equal to aggregate value of savings in the region. Aggregate savings in turn is derived from household behavior. (should be investigated further)

Limitations of the Polestar Framework

There is an important difference between Polestar and the global models introduced above: Polestar is not a dynamic simulation model, but static in the sense that all changes are introduced by the user. This provides on the one hand more flexibility to the user, but on the other hand, no checks for consistency or plausibility of the changes are done by the model.

Data sets uncertainty

1) OECD- countries
The base year data used for projections are taken from OECD Environmental Data Compendiums published by OECD in 1997 and 1999, for OECD countries. According to this source data is in some cases based on rough estimates and the projections bare these uncertainties.
Solid waste production is expensive to measure at source; thus, consistent and comparable statistics to feed the models are difficult to obtain.  It is unclear whether the data sets for  the model distinguish between toxic and hazardous wastes, and other; It is also unclear whether it covers waste stored on site.  Some times it is confused with the amount of solid waste disposed, which is measured by recording the weight or volume of waste disposed at the disposal or treatment site.    
Volume of waste produced may be significantly affected by the presence of particular wastes.  For example, the inclusion of construction wastes in domestic refuse will greatly affect the waste density and hence the indicator.  The actual method of storage of waste and its moisture content will also affect the waste density.  The volume of waste produced is often affected by seasonal variations in the production of various agricultural foodstuffs.

2) non-OECD countries
The base year input data on waste generation in non-OECD countries come from Doorn M.R.J and M.A. Barlaz. For most countries, data on total waste in place are not available and had to be developed from waste generation rates. The total annual waste generation rate (Tg/yr) is obtained by multiplying Municipal waste generagtion rates with population data.  Per capita MSW generation rates range from 1.7 to 1.9 kg/day for the U.S. and Canada. Per capita MSW generation rates in other developed countries are about 1.2 kg/day (also for Europe?). For developing countries, rates are about 0.8 kg/day for urban, and 0.3 kg/day for rural areas. Substantial uncertainty in the global estimates from this source results from a lack of data characterizing (1) country-specific waste generation, (2) waste management practices.

Rationale uncertainty

No uncertainty has been specified