Drivers and Barriers for the Adoption of Circular Economy Principles towards Efficient Resource Utilisation
To obtain a common understanding of what it means to be “circular” in an economy, revisiting the essence of a circular economy (hereafter ‘CE’) is important, as this concept is trending and thus tends to diffuse in interpretations.
Developing a modern framework for enforcing CE requires a multidisciplinary approach that incorporates the current economic, ecological, and social pillars of sustainable development. To effectively implement this concept, it is necessary to examine various factors that impact it and determine their extent and influence.
The paper aims to (1) identify the key factors that can help accelerate the establishment of circularity in the observed environment through coordinated and joint action, emphasise the significance of creating systematic indicator sets, and give propositions to measure them in a new approach; (2) analyse 9R circularity strategies in detail; (3) study and upgrade the circular material use (CMU) rate introduced in the European Union and, based on material data calculation, obtain a modified formula based on financial data; and (4) perform analysis of the proposed new equation using publicly available statistical data.
Perhaps the reason for the rare attempts to consider circularity based on higher levels of the waste management hierarchy is the very complexity of the tasks.
2. Materials and Methods
Even with the loosening of the shackles of the linear economy, several influential factors related to existing producer–consumer relations may slow down the transition to CE. There are limited established regulations and conformity procedures for CE activities.
The literature presents different understandings of barriers according to their influence on accepting circular economic principles.
When considering potential factors that can encourage or prevent the implementation of CE, it is essential to be guided by the characteristics of the area where the principles of the CE are implemented.
Analysing sector-specific relationships among stakeholders can help overcome circularity implementation barriers, and the next step can be determining the protocols proposed to fit and standardise the data for further analysis of the existing system.
The primary challenge is that the metrics are not yet satisfactorily developed to follow the CE transformation process. One of the first issues is whether the results on the level of circularity achieved in material resource management can be simplified into a single numerical value. The goal should be to enable a more direct comparison of the realised level of circularity of systems of the same rank.
One single number should represent the circularity of material resource management within the observed system.
2.1. Structure of the Indicator Framework
Overall recycling rates: recycling rates for (a) municipal waste (%) and (b) all waste excluding major mineral waste (%);
Recycling rates for specific waste streams: recycling rates for (a) packaging, (b) plastic packaging waste (%), and (c) electrical and electronic equipment waste that is separately collected (%).
Contribution of recycled materials to demand for raw materials: (a) circular material use rate (%) and (b) end-of-life recycling input rates (%);
Trade in recyclable raw materials: (a) imports from outside the EU, (b) exports outside the EU, and intra-EU trade (all three in tonnes).
2.2. Measuring Circularity
Measuring circularity through the development of circular metrics can be a powerful way to bring visibility to different elements of observed systems.
After examining the present circular metric scenarios, some critical insights can be identified:
Operationalising circular strategies involves various actors and activities across the value chain (from suppliers and manufacturers to service providers and reverse logistics partners). In order to identify areas for improvement, it is necessary to measure and attribute the collective and individual impacts at both the product and company levels .
Various factors directly influence circularity. These factors should be considered when measuring circular metrics. Some are servisation (i.e., provision of a service rather than ownership); digitalisation; and product design for modularity, repairability, disassembly, and reuse . However, determining the appropriate boundaries for measurement can take time due to the involvement of multiple actors and factors in the value chain.
To fully capture the multidimensional nature of circularity, metric frameworks must standardise terminology and definitions, set quantifiable baselines for relative comparisons, and find practical solutions to improve data availability and quality. Maturing frameworks will require collaboration among companies and developers to develop key indicators and standardise definitions. In order to simplify processes, frameworks should enable measurement at the product group or category level.
The concept of a sustainable CE introduces a fresh economic model that prioritises “multidimensional progress” rather than solely focusing on GDP growth. This model seeks to improve the environment, enhance human well-being, and promote economic prosperity for present and future generations.
Already established metrics based on material flow should be kept in place. Additionally, circularity should be assessed through indirect metrics. It is interesting to calibrate indirect metrics of CE in areas where direct methods based on material flow are impossible.
The easiest part is to monitor the material flow, but even this part needs to be completely covered and secured in terms of accurate results. A problem is metrics that assess the CE accomplishment in areas without material flow. The authors of this work propose a metric system based on direct data already made available by statistics offices based on financial flow.
It helps track the percentage of material that has been recovered and reintroduced into the economy, therefore reducing the need to extract virgin materials.
In order to also assess the circularity for non-material flows, it is proposed to transform Equation (1). After the transformation, the equation should produce the same results as those already adopted by the EU for material flows and based on available statistical data. The reason for the transformation is to be able to make the calculations based on financial data available for most CE approaches. Based on that, it is possible to produce a joint value of utilised CE approaches.
Equation (5) still produces the same results as Equation (3) and is based on the same material flow data.
where the following definitions hold:
—the financial value of recycled materials based on the domestic material consumption price and mass share of recycled materials compared to fresh domestic materials;
—the financial value of domestic material consumption.
Equation (7) combines the financial value of material flow with material flow itself, and Equation (7) produces the same results as Equation (1) or Equation (3), which are based on material flows only. This equation allows utilising the financial values if the material flow is not known. The only limitation is the same or at least comparable price of fresh and recycled materials per mass.
This approach to switching from material flows to financial data allows calculating CE ratings and evaluating CE approaches that can only be assessed financially.
The strategies (R3–R7) related to the extended lifespan of the product and its parts are reuse, repair, refurbish, remanufacture, and repurpose. The strategies sometimes overlap in real life, but the only thing important is not to include the same strategy more than once in an index calculation.
When combining more indicators, like in the case of 9R, they should be put on the same denominator and can be added together. This approach is only possible with the money value as a unit. All other units do not cover all principles of CE. Even with keeping track of the financial flow, some CE solutions will have to be financially assessed indirectly.
In order to include all Rs in Equation (8), it is crucial to follow the instructions on calculating the amount of money intended for each R in the past year. Only direct expenditures for the product can be included to avoid multiple circularity effects in the production value chain. Also, expenditures utilised for one R cannot be used for another R.
The Rs should be calculated as follows:
R0—Turnover with a radically different product for the same function with the addition of last year’s turnover product that was abandoned.
R1—Turnover with products designed for sharing or multi-functional use.
R2—Money saved on increased efficiency and saved natural products and materials. Also, the money is spent on secondary raw materials instead of natural materials.
R3—The “new value” of reused products.
R4—The turnover of the repair (service and spare parts). It should include authorised and unauthorised services and parts.
R5—Money saved by restoration compared to a “new product”.
R6—The volume of sales/purchase of remanufactured parts.
R7—The volume of sales/purchase of repurposed parts.
R8—The volume of sales/purchase of recycled materials.
R9—The value of recovered energy.
The “product” in Equation (8) is either a material product or service.
The proposed approach, implemented only for nine R strategies, can be broadened to complete the system.
There is a trade-off between the simplicity and accuracy of the circularity indicators. More clear indicators may be easier to communicate and understand but may not capture circularity’s full complexity and diversity. More accurate indicators may require more data and assumptions, but they may be more challenging to communicate and understand. Ultimately, policymakers will decide on the necessary complexity of data for official measurements of CE.
There is a risk of unintended consequences or rebound effects of circularity. When measuring circularity, it is essential to consider the system lifecycle and its interactions with other systems. For instance, increasing the recycling rate of a material may lower its environmental impact. However, it can also raise its demand and price, resulting in more primary resource extraction.
To apply the proposed Equation (8), it was decided to use the data on passenger cars in selected EU countries. Unfortunately, not all data for all states were available. The decision was still to perform calculations for one large EU country, one of the wealthiest countries of the EU, one middle-income EU country, and one below-average-income EU country. The EU countries that have been selected for further calculation are Gerseveral, Ireland, Slovenia, and Croatia.
Most of the Rs are applicable to passenger cars. R6 (Remanufacture) and R7 (Repurpose) were not considered since both are not applicable to passenger cars on the EU market due to strict traffic rules for their use on public roads.
R4 (Repair) is estimated using the turnover of passenger car service companies and spare parts sold. In low-income countries, service, especially on older cars, is not performed by service companies and thus is not included in unofficial statistics and can be only assessed through sales of spare parts.
The results show that the most influential approaches for passenger cars are reduction, reuse, repair, and refurbishment. A comparison among the countries shows that they can be further enhanced in countries with relatively lower percentages. Some approaches like car-sharing are still developing in terms of volume but offer great opportunities.
Equation (8) for CEIR calculation is based on some assumptions that were needed to establish the financial volume of a single CE approach for passenger cars. These assumptions will be further improved, and that will make CEIR results different. But now it already is possible to compare countries, making the richest countries in comparison the worst performing.
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