RUDN University economists have developed an approach for assessing the development of the circular economy in different countries. The new method will help experts and governments determine how successfully waste recycling systems, energy-saving technologies and new green materials are being introduced into the economy. The results are published in Sustainability.
Newswise — Experts in sustainable development define the traditional economy as linear: resources are taken from nature, goods are produced from them, waste from production and consumption lies in landfills or is destroyed. In contrast, a circular economy assumes that resources consumed are returned to the production cycle, and renewable energy sources are used instead of fossil fuels. According to some forecasts, by 2030 the transition to circular economy will reduce the consumption of natural resources by 53%, and by 2050 – by 83% to reduce carbon dioxide emissions.
“Circular economy approaches are being implemented by many countries of the world. But it is difficult to assess the global success of these innovations since there are no standard indicators of the “cyclicity” of the economy. There are no indicators that would say: in this country, the economy has become a circular economy by 30%, and in this country – by 60%. This limits both the possibility of international comparisons and the dissemination of successful practices,” said Konstantin Gomonov, PhD, Associate Professor of the Department of Economic and Mathematical Modeling of the RUDN University.
RUDN University economists have proposed a new solution to this problem: statistical approach for assessing the development of a circular economy in different countries. To do this, they tested several clustering algorithms on the example of the European Union countries. Such algorithms group objects (in this case, countries) into clusters that are close to each other by the selected indicator. The aim of the study was to group countries according to the effectiveness of the introduction of a circular economy.
In the calculations, the RUDN economists used data from the EU monitoring system, which takes into account the volume of production and consumption, as well as waste and recycled materials. For example, they chose two statistical indicators: the volume of residential waste per capita and the total amount of waste per unit of GDP, excluding waste from extractive industries. If the economy produces a minimum of non-recyclable waste, it means that the resources in it are used as efficiently as possible.
The k-means method showed the greatest efficiency for the task. This popular clustering algorithm is based on splitting a set of objects into a given number of clusters. At each step, they are mixed until the intra-cluster distances — the difference between objects according to the selected indicator – become minimal. At the same time, only one of the tested indicators was eventually recognized as suitable. Data on household waste per capita can reliably divide countries by the level of development of the circular economy, while information on the total amount of garbage is more often incomplete and unreliable.
The result of the work was a software module which can classify economies and visualize the results. The application of the algorithm to European countries made it possible to divide them into four internally homogeneous clusters. According to the conclusion of the RUDN economists, Belgium, Croatia, Hungary and Turkey use the most effective practices of introducing a circular economy.
“Although our study of European countries was conducted primarily to test the chosen approach, it showed a realistic picture of the introduction of a closed-loop economy in these states. For example, we saw that high GDP here is not a guarantee of success,” said Konstantin Gomonov, PhD, Associate Professor of the Department of Economic and Mathematical Modeling of the RUDN University.
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