• Energy Research
• Closed Access close
• Restricted close
• 8. Economic growth close
• HR close
• BG close

The general aim of circular economy is the most efficient and comprehensive use of resources. In order to achieve this goal, new approaches of Industry 4.0 are being developed and implemented in the field of waste management. The innovative K-project: Recycling and Recovery of Waste 4.0 - "ReWaste4.0" deals with topics such as digitalisation and the use of robotic technologies in waste management. Here, a summary of the already published results in these areas, which were divided into the four focused topics, is given: Collection and Logistics, Machines and waste treatment plants, Business models and Data Tools. Presented are systems and methods already used in waste management, as well as technologies that have already been successfully applied in other industrial sectors and will also be relevant in the waste management sector for the future. The focus is set on systems that could be used in waste treatment plants or machines in the future in order to make treatment of waste more efficient. In particular, systems which carry out the sorting of (mixed) waste via robotic technologies are of interest. Furthermore "smart bins" with sensors for material detection or level measurement, methods for digital image analysis and new business models have already been developed. The technologies are often based on large amounts of data that can contribute to increase the efficiency within plants. In addition, the results of an online market survey of companies from the waste management industry on the subject of waste management 4.0 or "digital readiness" are summarized.

Energy efficiency has been among the key objectives of the energy policy of the European Union and the European Structural and Investment Funds in the 2014–2020 programming period. It is one of the key priorities of the new European Green Deal, which will guide the EU programmes in the next multiannual financial framework. To provide recommendations for national Managing Authorities on how to design energy efficiency measures for enterprises in the 2021–2027 period, the paper assesses the effectiveness and efficiency of a small- and medium-sized enterprises (SME) support scheme in Bulgaria, which has received financing of more than EUR 150 million under the European Regional Development Fund. Combining data from publicly available databases, the paper provides an analysis of geographical and sectoral distributions, the ratio between grant size and energy savings (unit costs), estimations of correlation coefficients and linear regressions, and simple payback time of the EU-financed projects. The key finding of the study is that the scheme under Operational Programme ‘Innovation and Competitiveness’ did not score the input/output ratio of project applications, which resulted in very diverse unit costs, and some of the reviewed projects produced very low energy savings. Overall, the data show that the EU support for energy efficiency measures of large enterprises under the same programme was more coherent and cost-effective as compared to the SME procedure. The paper puts forward recommendations for designing energy efficiency support schemes, which relate to the assessment criteria, the use of internal benchmarking to assess efficiency, and the payback time of energy efficiency measures.

As the digital economy develops rapidly and the network information technology advances, new development models represented by the network economy have emerged, which have a crucial impact on green economic growth. However, the relevant previous studies lacked the role of analyzing the direct and indirect effects of internet development on green economic growth at the prefecture-level city level. For this purpose, this paper aims to examine the intrinsic mechanism of the impact of internet development on green economic growth and provide empirical support for cities and regions in China to increase internet construction. Furthermore, the mixed model (EBM), which includes both radial and non-radial distance functions, is applied to calculate the green economic growth index. Fixed effect model and mediation effect model are also employed to test influence mechanisms of the internet development on green economic growth using panel data of 269 prefecture-level cities in China from 2004 to 2019. The statistical results reveal that internet development has contributed significantly to green economic growth. When the internet development level increases by 1 unit, the green economic growth level increases by an average of 5.0372 units. However, regional heterogeneity is evident between internet development and green economic growth, that is, the promoting effect of internet development on green economic growth is gradually enhanced from the eastern region to the western region. We also find that internet development guides industrial structure upgrading improves environmental quality and accelerates enterprise innovation, which indirectly contributes to green economic growth. And internet development mainly achieves green economic growth through enterprise innovation. Based on the above findings, we concluded that policymakers should not only strengthen the guiding role of social actors to promote the stable development of the internet industry, but also foster the construction of the three models of "internet+industry integration," "internet+environmental governance," and "internet+enterprise innovation" to promote green economic growth.

The key issues concerning oil exploitation are still open for discussion: there is no agreement about where we presently stand in the world oil extraction curve, what is its exact shape, and how far can oil price grow before it changes irreversibly the world economy and consumer behavior. The paper proposes an alternative scenario to the Hubbert's bell-shaped model of oil exploitation, based on more realistic assumptions regarding political agendas in oil-exporting countries and consumer behavior dynamics in oil-importing countries. Under this scenario, the joint impact of markets and public policy in oil importing countries together with “resource pragmatism” policy in oil-exporting countries allows for a less steep oil supply curve with a much fatter tail compared to the Hubbert's model.

BRICS are among the rising nations which drive economic growth by excessive utilization of resources and resulting in environment degradation. Although there is bulk of research on environmental Kuznets curve (EKC), very limited studies explored the scope in context of tourism in BRICS countries. So this research is conducted to explore the association of tourism, renewable energy, and economic growth with carbon emissions by using annual data of BRICS countries from the year 1995 to 2018. By using the recent approach of method of moments quantile regression (MMQR), the finding shows that tourism has stronger significant negative effects from 10th to 40th quantile while the effects are insignificant at remaining quantiles. Furthermore, an inverted U-shape EKC curve is also apparent at all quantiles excluding 10th and 20th quantiles. For renewable energy, the results are found negatively significant across all quantiles (10th-90th) which claim that CO2 emission can be reduced by opting renewable sources. Hence, the empirical results of the current study provide insights for policymakers to consume renewable energy sources for the sustainable economic growth and solution of environmental problems.

The Belt and Road Initiative (BRI) is a significant economic development strategy directed by China. Its primary objective is to establish connectivity across a vast region encompassing over 70 countries in Asia, Europe, and Africa. This endeavor significantly impacts worldwide development, economic advancement, and environmental sustainability. Nevertheless, insufficient pertinent evidence exists when exploring the correlation between urbanization, rural energy poverty (Rural_EP), and carbon emissions (CO2_Em) in the BRI region. The present study examines panel data encompassing 48 countries participating in BRI from 2001 to 2020. This research addresses existing gaps by employing the System-GMM and Driscoll and Kraay Standard Error (DKSE) models to investigate factors influencing CO2_Em. The findings indicate that the presence of energy poverty in rural areas is associated with higher levels of CO2_Em, while urbanization has a mitigating effect on such emissions. Furthermore, adopting production methods and environmentally sustainable technologies by foreign corporations leads to a decrease in CO2_Em, thereby providing evidence of a pollution halo effect in BRI. Moreover, economic growth and industrialization have detrimental environmental consequences, primarily through the amplification of CO2_Em. Based on the empirical evidence, the study proposes policy measures that advocate for promoting renewable energy sources, adopting sustainable urban development practices, implementing energy conservation strategies, and establishing carbon pricing mechanisms.

The endeavor to implement the 2030 Agenda of national and international stakeholders became increasingly impetuous, considering the wide range of uncertainties and risks. The new humans-centered development model built on the prominence of environmental and social values seeks to reinforce communities' resilience and mitigate environmental risks, leaving no one behind. For this to happen, solid and effective institutions, the right environmental policies, and a safe statutory labor framework are the sine qua non. In this study, we evaluated the effects of informality, institutional quality, and renewable energy consumption on ecological footprint of two groups of emerging countries from Europe and Asia from 2002 to 2018. Our results by PMG-ARDL approach highlight dissimilarities between the two groups, showing greater heterogeneity. In this sense, informality is found to have positive and significant effects on ecological footprint in the long run in emerging European countries. In contrast, the effect is negative for emerging Asian countries. In the short run, the effects are less critical in the studied countries between the two groups. Institutional quality variables impacted environmental quality differently. In this sense, it is detrimental for policymakers to consider concerted measures to decrease institutional vulnerabilities and reduce the level of the informal economy. The outcome of this study concurs with a complete awareness of the importance of informality and institutional quality to mitigate social and environmental risks conjunctively.

Globally, the rising concentration of anthropogenic greenhouse gases emission in the atmosphere is extremely detrimental to the environment. The high concentration among all greenhouse gases is carbon dioxide emission. Therefore, this study explores the linkages between energy consumption, trade openness, globalization, urbanization, and carbon dioxide emission for Malaysia over the spans from 1978 to 2018. ARDL bound testing model was employed to investigate involvement in the elevation of carbon dioxide emissions in the economy. The study illustrates that a 1% growth in energy consumption, trade openness, and urbanization will deteriorate the environment by 0.18%, 0.03%, and 2.51% respectively. Further, variance decomposition analysis predicts that all the determinants in the study have significantly caused carbon dioxide emission in Malaysia. The paper presents scientific support for further studies and argues for the use of innovation shocks as a policy instrument for a prosperous future by formulating more successful environmental policies.

This study aims to explore the driving determinants on the export-related carbon intensity (ECI) of China, to better understand the impact of international trade on climate change governance and facilitate China's carbon intensity mitigation goals. First, China's ECI evolution and its gaps with the USA and India are measured during 2002-2014. Then, the main drivers of China's ECIvert study further discusses the influencing factors of ECI in the manufacturing industry using the environmental-extended STIRPAT model and GMM method. The results show that (1) China's overall ECI increases from 1.50 Kg/US$ in 2002 to 1.92 Kg/US$ in 2005 and then decreases to 1.27 Kg/US$ in 2014. The ECI of the manufacturing industry is significantly higher than that of the agriculture and service industry. China's ECI gap with the USA is greater than that with India, and both show a downward trend. (2) Carbon emission coefficient is the domain factor to reduce China's ECI during 2002-2014; the effects of the value-added coefficient, input-output structure, and final demand are limited. The input structure dominantly expands China's ECI gaps both with the USA and India, followed by the value-added coefficient. The carbon emission coefficient enlarges the ECI gap with the USA while reduces that with India. (3) Industrial productivity and value-added rate are negatively correlated with ECI in the manufacturing industry, while per capita capital stock plays the opposite role. The positive correlation between energy intensity and CIE becomes significant after distinguishing technology heterogeneity. In contrast to the non-tech-intensive manufacturing industry, the increase of backward GVCs participation of tech-intensive ones will reduce the ECI. The threshold effect of backward GVCs participation exists in the whole manufacturing industry. Targeted ECI reduction policy implications are suggested.