In the European Union, basic strategy results from the need to provide intelligent, sustainable, and inclusive growth, along with respect to social and economic impacts of waste treatment. The paper focuses on municipal waste and its separation. Generally, within global waste management initiatives, the main goal is to minimize the negative effects of waste on the environment, as well as to increase and optimize the sources’ efficiency in the waste economy. Research on municipal waste development and its separation was done in individual regions of Slovakia to find if socially weaker regions have worse waste treatment. The results were compared according to the waste development per inhabitant and per household, as well as through rate indexes, which are connected to relationships between waste, social, and economic indexes. The results confirmed research results from other countries that show that the volume of municipal waste is increasing due to increased living standards of inhabitants. However, on the other hand, waste separation rates also increased—mainly based on the legislative support.
The European Commission has established a Critical Raw Materials List (CRM) for the European Union (EU), which is subject to regular review and updating. CRMs are needed in many key industries such as automotive, steel, aerospace, renewable energy, etc. To address this issue, we studied publicly available data from databases developed by the EU for monitoring the progress of individual countries in key areas for the development of society. The paper analyzes indicators of import reliance, net additions to stock, domestic material consumption (DMC), resource productivity, and circular material use rate. Prospective products and technologies, in electromobility, digitalization, Industry 4.0, and energy transformation, are changing and increasing the demand for raw materials. The aim of this article is to look at the ways forward in order to use critical raw materials as efficiently as possible while at the same time ensuring the optimal economy of the countries. From the sources and databases of data available for the EU, we analyzed a number of variables and suggested options for future developments in the efficient use of critical raw materials. We defined what we believed to be the optimal management means in relation to critical raw materials and worked backwards to find a path to efficient use of critical raw materials.
The constant rise in the consumption of resources puts the environment under pressure. Most resources are non-renewable in nature, which is why they must be utilized with great care. For this reason, the European Union devotes increasingly more attention to their efficient use. It deals with these aspects, making an effort to maintain the long-term competitiveness and to secure sustainable development in line with all of the related environmental impacts. In this context, several goals have been set out, to which the individual EU member states are bound. A method for monitoring resource efficiency was developed, consisting of indicators, the aim of which is to assess the efficiency of the use of soil, water, energy, with the most fundamental one being resource productivity. The results of the efficiency of use of the individual resources in the member states greatly differ, even without further investigating the links and correlations between the indicators. Research on the interrelationships of the individual indicators in terms of mutual influence has not yet been completed. The aim of our study was to define the correlation between the main indicator, resource productivity, and the other indicators at the level of the EU and its member states. For this purpose, we prepared a database with data which, for the sake of uniformity, were obtained from the publicly available Eurostat database. Subsequently, the data were analyzed and evaluated using the statistical software JMP 15 by a regression and correlation analysis. By using the multiple regression analysis, we created a model describing the significance of the impact of the observed variables on the resulting resource productivity of the EU member states. Generally, there is a positive correlation between the resource productivity and the Eco-Innovation index, as well as the utilization rate of recycled materials. For the sake of comparison, we developed a regression model at the level of the V4 countries, with the aim of evaluating the impact of the historical background of the countries on their contemporary ability to reach the goals set out by the environmental policy. The V4 countries are lagging far behind in meeting all of the environmental policy objectives, not only in tracking the main indicator (resource productivity) on which the multiple regression analysis is based. It was interesting to find that the multiple regression model at the V4 level does not include the indicators defined by the EU level model, the key ones, in this case, being water productivity, energy dependence, energy productivity, and environmental tax. This finding may also, after further analyses, be the key for other countries joining the EU in the future, in defining the weaknesses of the newly acceding states in terms of the EU’s move towards a circular economy.
A businesses with a green label is associated with resources that are sustainable. This business is linked to the green economy, which can be described as a form of economy that is responsible in relation to the environment and economic growth, and thus complementary. In this type of economy, viable products are created, but also solutions and practices that take the environment into account. It is well known that eco-innovation activities are closely linked to the development of an eco-business. The research sample consisted of 10 countries, namely the Slovak Republic, the Czech Republic, Poland, Hungary, Austria, Germany, France, Italy, Sweden, and Finland, which were selected by purposive sampling. In this article, we look at eco innovations in selected countries, specifically ranking them, where we have divided countries into different levels, from countries that are at the super eco-innovation level, to countries that are in the middle zone, to countries that are significantly lagging in this trend. To classify countries into each level, we looked at the following variables: eco-innovation inputs, eco-innovation activities, environmental outcomes, socio-economic outcomes, and the eco-innovation index itself. Taking these sub-results into account, we determined where countries are, in other words, which level they have reached. We found that there are significant differences between countries. As we conclude, there are several reasons for this, but one of them is the lack of communication, coordination, and synergy between institutions, government, and SMEs, which are the drivers of eco-innovation. The supporting quantitative data collection method was data collection and structured observation, which is more precise and therefore provides more detailed information about the reality under study. For the purpose of this thesis, data were obtained from the Statistical Office of the European Union, that is, Eurostat, which is responsible for publishing pan-European statistics and indicators that allowed us to compare countries. In the survey, we compared the five most recent years for which Eurostat data were available, namely 2017, 2018, 2019, 2020, and 2021. The overall score of a European Union member state is calculated as the unweighted average of 16 sub-indicators. It shows how well each Member State performs in terms of eco-innovation compared to the European Union average of 100.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.