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Indicator Assessment
Municipal waste generation is still increasing in OECD countries, but at a slower pace since 2000. There has been a relative decoupling of municipal waste generation in OECD countries from economic growth, but waste generation is continuing to increase.
OECD country municipal waste generation, 1980-2030
Municipal waste generation within the OECD area
Note: N/A
OECD: Municipal waste generation within the OECD area and its regions, 1980-2030
OECD Countries
Table 1 provides data and projections from 1980 to 2030 for population, real GDP, and generation of municipal waste for the OECD and its regions. OECD data for municipal waste exist for 1980-2005, and these form the basis of the OECD Outlook projections to 2030.Within the OECD region, the increase in municipal waste generation was about 58% (2.5%/year) from 1980 to 2000, and 4.6% (0.9%/year) between 2000 and 2005 (Table 1). During the latter period, the number of OECD households increased by some 4% (0.8%/year) (OECD estimate), population increased by 3.6% (0.7%/year), GDP grew by 11% (2.2%/year), and private final consumption (PFC) rose by 13% (2.6%/year). These data therefore suggest a rather strong relative decoupling of municipal waste generation from economic growth . However, the observed reduction in the growth of municipal waste generation with respect to economic growth between 2000 and 2005 may not really reflect an improving situation.
Using these assumptions, and assuming no new policies, the generation of municipal waste is projected to increase from 2005 to 2030 within the OECD region by 38% (1.3%/year). This is less than the projections that were made in 2001, reflecting the recent downturn in municipal waste generation (OECD, 2001a; OECD, forthcoming). In 2001, it had been estimated that there would be some 835 million tonnes of waste being generated annually by 2020; it is now estimated that this figure will be closer to 800 million tonnes. A recent projection by the European Topic Centre on Resource and Waste Management (ETC/RWM, 2007b) seems to support the new estimate, since it projects that (within the EU15) the generation of municipal waste will increase by only 33% to 2030. However, in the new EU member states, municipal waste generation is projected to grow faster than this - by about 66% to 2030. The primary variable explaining the increase in municipal waste generation within the ETC/RWM projections was either the total final private consumption or the sub-categories of final private consumption such as food, beverages and clothing (ETC/RWM, 2007b).
The annual per capita generation of municipal waste within OECD countries seems to be stabilising. It was 556 kg in 2000 and 557 kg in 2005. However, if municipal waste generation increases by 38% (and population by 11%) between now and 2030, as projected here, municipal waste generation per capita will increase to 694 kg in 2030 (up 25% from 2005) (OECD, forthcoming).
Municipal waste management practices vary widely among OECD countries. In the mid-1990s, approximately 64% of municipal waste was destined for landfills, 18% for incineration, and 18% for recycling (including composting) (OECD, 2001a). In 2005, the situation looked rather different, with only 49% of municipal waste being disposed of in landfills, 30% being recycled or composted, and 21% being incinerated or otherwise treated (OECD, forthcoming). Even more remarkable is that not only did the relative share of landfilling decrease considerably within OECD countries during this 10-year period, but the absolute amount of landfilled waste also apparently decreased almost 8% (from 346 to 320 million tonnes per year). Even so, in 2005, seven OECD countries still landfilled more than 80% of their municipal waste, and two did so for almost all of their waste (OECD, forthcoming). On the other hand, six countries landfilled less than 10% of their municipal waste in 2005, and another six countries considerably reduced their landfilling rate between 1995 and 2005 .
The OECD (2001a) projected that about 45% of municipal waste within the OECD area would be landfilled in 2020, 25% would be incinerated, and 30% would be recycled or composted. Since most of the current waste management policies, such as diversion of biodegradable waste from landfills within the EU, will be implemented by 2020, it is assumed here that the recycling rate will continue to increase until 2020, but will then gradually slow down in the Baseline situation. In fact, it has been observed in the US that the recycling rate of municipal waste in 2005 was already about 32% - up from 16% in 1995. In EU15, the recycling rate in 2005 was about 41% - up from 22% in 1995. Hence, it is assumed here that recycling will continue increasing within OECD countries, and will reach an average rate of 40% in 2030. However, the recycling rate may increase even more rapidly than this, due to the emerging recognition of the economic and environmental benefits of recycling, compared to other waste management options.
Non-OECD Countries
In 2030, the non-OECD area is expected to produce about 70% of the world's municipal waste, mainly due to rising incomes, rapid urbanisation, and technical and economic development (UNEP, forthcoming; World Bank, 2005). It is estimated that in 2030 the mean daily per capita municipal waste generation will be 1.8 kg in the OECD region, about 0.75 kg in the BRICS countries, and about 0.9 kg in the rest of the world (ROW). Total annual waste generation in 2030 is projected under the Baseline to be about 900 million tonnes for OECD countries, about 1 billion tonnes in the BRIICS countries, and around 1.1 billion tonnes in the rest of the world (ROW).
Some BRIICS countries (Brazil, Russia, Indonesia and South Africa) have already exceeded the estimated mean daily generation of municipal waste (0.75 kg/capita/day) that is projected for 2030 for this grouping of countries, although China and India still have a long way to go in this regard. On the other hand, municipal waste generation in urban China is already some 444 kg/capita/year (1.2 kg/capita/day), while the generation rate in rural areas is largely unknown.8 However, increasing incomes, rapid urbanisation, population and GDP growth will greatly accelerate municipal waste generation rates in India and China. It is estimated that in 2030 some 60% of the Chinese population will live in urban areas; in India, the urbanisation rate will be about 35%. Thus, in 2030 in China, annual urban municipal waste generation is expected to be at least 485 million tonnes (up 214% from 2004). In India, it will be around 250 million tonnes (up 130% from 2001; World Bank, 2005). This would mean that the daily per capita generation of municipal waste would be 1.5 kg in urban China, and 1.4 kg in urban India.
Considering the huge increase in municipal waste generation expected in non-OECD countries by 2030, appropriate management of this waste will be an enormous policy challenge. This will likely require that integrated waste management practices be introduced and that the large number of informal waste recyclers be integrated into the official waste management infrastructure (McDougall et al., 2001; World Bank, 2005).
Key uncertainties and assumptions
The GDP and population trends contained in Table 1 are from the economic Baseline for this Outlook (see Chapters 2 and 3 of the OECD Environmental Outlook 2008). Historical trends of municipal waste generation in the OECD and its regions have been calculated on the basis of OECD data (OECD, forthcoming). Waste generation projections in Table 1 have been extrapolated from observed municipal waste generation between 2000 and 2005. The figures for OECD and its regions in Table 1 are partly taken from Table 1, and partly calculated on the basis of Table 1 figures. The figures for BRICS countries and the rest of the world (ROW) have mainly been calculated on the basis of municipal waste generation figures found in the literature.
In general, the lack of frequent, consistent and reliable waste data remains a serious problem. For the OECD, only the data on municipal waste allows the establishment of trends, and even these may be questioned. The most recent OECD data (OECD, forthcoming) indicate that the increase in generation of municipal waste has been considerably reducedin 2000-2005, compared to previous years. However, this may not necessarily reflect the real situation, especially given that the conclusion seems inconsistent with recent trends in the economic or social "drivers" of municipal waste generation. It could be that the observed breaks in time series of several countries' data during this time-frame partly cause the lower trends. It is also possible that municipal waste has become "lighter" over the years (with more packaging and related reductions in food waste volumes), but there is no convincing data to support this hypothesis. Another explanation could be that some of the household waste (e.g. bulky waste, electric and electronic appliances), as well as commercial waste, are increasingly escaping municipal waste statistics, perhaps because they are returned to retailers or submitted to private industrial waste management systems.
There are also weak indications that the generation of hazardous waste is increasing within the OECD area, but (due to missing time series) this cannot be verified. Concerning the non- OECD countries, the situation is even more unclear, since practically no time-series data exist. Therefore, the values presented in Table 1 are "educated guesses" of the current and future status of the non-OECD municipal waste generation and management problem. The order of magnitude is probably broadly correct, but the details remain highly uncertain.
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
Global and Pan-European policy context
No international agreements exist for reduction in solid waste production.
The European Neighborhood Policy, STRATEGY PAPER
EU level
Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste
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.
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).
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.
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.
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.
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.
No uncertainty has been specified
For references, please go to https://www.eea.europa.eu/data-and-maps/indicators/municipal-waste-generation-outlook-from-oecd/municipal-waste-generation-outlook-from or scan the QR code.
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