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Rare earth elements (REE) are widely used in high technologies, medical devices, and military defense systems, and are especially indispensable in emerging clean energy. Along with the growing market of green energy in the next decades, global demand for REE will increase continuously, which will put great pressure on the current REE supply chain. The global REE production is currently mainly concentrated in China and Australia; they respectively contributed 85% and 10% in 2016. However, there are 178 deposits widely distributed in the world, and reported REE resources as of 2017 totaled 478 megaton (Mt) rare earth oxides (REO); 58% of these deposits contained exceed 0.1 Mt REO; 59 deposits have been technically assessed. These resources could sustain the global REE production at the current pace for more than a hundred years. It is noted that REE demand from clean technologies will reach 51.9 thousand metric tons (kt) REO in 2030, Nd and Dy, respectively, comprising 75% and 9%, while these two elements comprise 15% and 0.52% of the global REE resources, respectively. This indicates that Nd and Dy will strongly influence the development of exploring new REE projects and clean technologies in the next decades.

Global energy transition trends are reflected not only in oil and gas market dynamics, but also in the development of related sectors. They influence the demand for various types of metals and minerals. It is well-known that clean technologies require far more metals than their counterparts relying on fossil fuels. Nowadays, rare-earth metals (REMs) have become part and parcel of green technologies as they are widely used in wind turbine generators, motors for electric vehicles, and permanent magnet generators, and there are no materials to substitute them. Consequently, growth in demand for this group of metals can be projected in the near future. The topic discussed is particularly relevant for Russia. On the one hand, current trends associated with the global energy transition affect the country’s economy, which largely depends on hydrocarbon exports. On the other hand, Russia possesses huge REM reserves, which may take the country on a low-carbon development path. However, they are not being exploited. The aim of this study is to investigate the prospects for the development of Russia’s rare-earth metal industry in view of the global energy transition. The study is based on an extensive list of references. The methods applied include content analysis, strategic management methods and instruments, as well as planning and forecasting. The article presents a comprehensive analysis of the global energy sector’s development, identifies the relationship between the REM market and modern green technologies, and elaborates the conceptual framework for the development of the REM industry in the context of the latest global tendencies. It also contains a critical analysis of the current trends in the Russian energy sector and the plans to develop the industry of green technologies, forecasts future trends in metal consumption within based on existing plans, and makes conclusions on future prospects for the development of the REM industry in Russia.

The crucial role that financial markets have played in accelerating the shift to clean energy and renewable sources of energy is examined in this article. Thus, we built global essential mineral trade networks from 1999 to 2020 using a complex network technique to analyze their topological properties quantitatively. The impact of crucial mineral trade patterns on the growth of renewable energy is then examined using the dynamic econometric model, along with the mediating function of technological advancement in renewable energy. It analyzes investment patterns and possibilities in various industries while underlining the critical role that financial systems play in determining the speed and scope of the change. The research uses data from reliable sources and thoroughly analyzes the body of current literature. The data shows that investments in clean technologies and renewable energy have significantly increased recently. This increase may be ascribed to several causes, including favorable governmental regulations, falling renewable energy technology prices, and rising environmental consciousness among the general people. Venture capital, private equity, public markets, and specialist funds are just a few examples of financial markets that have been instrumental in directing funding to these industries. The report also reveals a change in how money is invested in the energy industry, with conventional investments in fossil fuels declining and investments in renewable energy growing significantly. The profitability and appeal of renewable energy projects, which are now competitive with traditional energy sources, are driving this transformation. The report also identifies new investment possibilities in clean technology, including smart infrastructure, grid modernization, and energy storage. Due to their potential to improve the effectiveness, dependability, and sustainability of energy systems, these areas are expanding. The results highlight the need to establish long-term stability and incentives for investment in the clean technology and renewable energy industries. Government assistance has considerably aided investor confidence, including carbon pricing systems, tax incentives, and subsidies for renewable energy sources. This analysis emphasizes how critical financial markets are to accelerating the energy transition. Financial markets may hasten the transition to a sustainable energy system by directing investments into clean technologies and renewable energy industries. To take advantage of the investment possibilities given by the energy transition, policymakers, investors, and industry stakeholders must work together.

The Sub-Saharan Africa (SSA) is far lag behind the sustainable targets that set out in the United Nation’s Sustainable Development Goals (SDGs), which is highly needed to embark the priorities by their member countries to devise sustainable policies for accessing clean technologies, energy demand, finance, and food production to mitigate high-mass carbon emissions and conserve environmental agenda in the national policy agenda. The study evaluated United Nation’s SDGs for environmental conservation and emission reduction in the panel of 35 selected SSA countries, during a period of 1995–2016. The study further analyzed the variable’s relationship in inter-temporal forecasting framework for the next 10 years’ time period, i.e., 2017–2026. The parameter estimates for the two models, i.e., CO 2 model and PM 2.5 models are analyzed by Generalized Method of Moment (GMM) estimator that handle possible endogeneity issue from the given models. The results rejected the inverted U-shaped Environmental Kuznets Curve (EKC) for CO 2 emissions, while it supported for PM 2.5 emissions with a turning point of US$5540 GDP per capita in constant 2010 US$. The results supported the “pollution haven hypothesis” for CO 2 emissions, while this hypothesis is not verified for PM 2.5 emissions. The major detrimental factors are technologies, FDI inflows, and food deficit that largely increase carbon emissions in a panel of SSA countries. The IPAT hypothesis is not verified in both the emissions; however, population density will largely influenced CO 2 emissions in the next 10 years’ time period. The PM 2.5 emissions will largely be influenced by high per capita income, followed by trade openness, and technologies, over a time horizon. Thus, the United Nation’s sustainable development agenda is highly influenced by socio-economic and environmental factors that need sound action plans by their member countries to coordinate and collaborate with each other and work for Africa’s green growth agenda.

This article presents the results of an analysis aimed at verifying the relationship between the implementation of SDG Goal 7 and the use of clean coal technologies in Poland. Clean coal technologies in the United Nations plans will constitute a crucial element of the strategy for sustainable development in the energy context. They are intended to be one of the tools for building an energy system based on renewable energy sources, constituting a bridge that enables the transition of Poland’s energy system from coal to renewable energy sources. To identify whether this relationship exists, the Autoregressive Moving Average with Exogenous Input (ARMAX) model was used. The structure of the model, its correctness, and its accuracy were confirmed using information criteria; statistical tests such as Dickey-Fuller, Doornik-Hansen, Durbin-Watson, and Breusch-Pagan; and measures of prediction accuracy such as MAPE, MAE, and RMSE. The explanatory variables were the Objective 7 indicators adopted by Eurostat. Before being introduced to the ARMAX model, they were standardized using the Compound Annual Growth Rate (CAGR) indicator. The analysis made it possible to indicate which of the explanatory variables has the greatest impact on the development of clean coal technologies in Poland, to determine a synthetic CAGR measure for all the explanatory variables, and to compare the results obtained with the indicator determined by the United Nations.

Existing frontier studies have predominantly focused on the incentivizing role of a single policy instrument, such as environmental regulations or government subsidies, in driving clean technology innovation. However, they have generally neglected to consider the impact of policy mix instruments on fostering clean technology innovation. This paper presents a mathematical deduction of the impact of environmental regulations, government subsidies, and their combined policy mix on clean technology innovation. Additionally, an empirical study is conducted using panel data from listed enterprises in China's clean energy industry spanning the period from 2008 to 2021. The findings reveal an inverted U-shaped relationship between both environmental regulations and government subsidies and the incentives for clean technology innovation, that is, they are characterized by promotion followed by suppression. Further analysis shows that a combination of environmental regulations and government subsidies positively promotes clean technology innovation. The results of the heterogeneity analysis indicate that environmental regulations and government subsidies have higher clean technology innovation performance for SOEs (state-owned enterprises), and the incentive effects of their policy mix are more significant. Moreover, in the eastern region, equal levels of government subsidies or environmental regulations yield higher incentives compared to the central and western regions, and the incentive effects of their policy mixes are more significant too. The findings of this paper will help policymakers flexibly design and implement incentive policies for clean technology innovation.

This systematic review investigates the role of artificial intelligence (AI) in advancing clean energy technologies within Europe, based on a literature survey from 2006 to 2023. The assessment reveals that AI, particularly through deep learning and neural networks, enhances the efficiency, optimization, and management of clean energy systems. Noteworthy is AI’s capacity to improve short-term energy forecasts, essential for smart cities and IoT applications. Our findings indicate that AI drives innovation in renewable energy, contributing to the development of smart grids and enabling collaborative energy-sharing models. While the research underscores AI’s substantial influence in Europe’s energy sector, it also identifies gaps, such as varied AI algorithm applications in different renewable energy sectors. The study emphasizes the need for integrating AI with emerging clean energy innovations, advocating for interdisciplinary research to navigate the socio-economic, environmental, and policy dimensions. This approach is crucial for guiding a sustainable and balanced advancement in the clean energy landscape, signifying AI’s pivotal role in Europe’s energy transition.

The present study draws motivation from the United Nations Sustainable Development Goals, with a special focus on SDGs 7 and 13, which highlight the need for access to clean and affordable energy in an environment devoid of emissions; it addresses climate change mitigation in the context of Sub-Saharan Africa. To this end, a carbon-income function setting for Sub-Saharan Africa (SSA) is constructed. The dynamic relationship between financial development and climate change is evaluated using three indicators and foreign direct investment and carbon dioxide emissions (CO2), while accounting for regulatory institutional quality using a “generalized method of a moment” estimation technique that addresses both heterogeneous cross-sectional issues. Empirical results obtained showed a positive statistical relationship between economic growth and CO2 emissions in SSA at the <0.01 significance level. This suggests that, in SSA, the economic growth path is pollutant emissions driven. This indicates that SSA is still at the scale phase of her growth trajectory. However, an important finding from the present study is that regulatory institutional indicators, such as political stability, government effectiveness, control of corruption, and voice and accountability, all exert a negative effect on CO2 emissions. This implies that regulatory measures militate against emissions in SSA. Based on the empirical findings of this study, it can be concluded that clean FDI inflows assist in ameliorating emissions. Thus, the need for a paradigm shift to cleaner technologies, such as renewables, that are more eco-friendly, is encouraged in Sub-Saharan Africa, as the current study demonstrates the mitigating role of renewable energy consumption on CO2 emissions. Further policy prescriptions are presented in the concluding section.

Currently, over 1.5 billion people, especially in the Global South, live without access to modern energy for household uses, especially for cooking. Therefore, this study examines the cooking space of the Global South with a specific focus on the rural communities to map alternative energy sources, technologies and supporting policies to drive clean cooking services for improved socioeconomic development. It begins with a literature review on clean cooking technologies and clean energy access for the Global South, which leads to the suggestion of clean cooking policies by mapping technology, affordability, accessibility, climate action, business model and local capacity. In order to ensure that the validation is appropriate, three online questionnaires were designed to capture three categories of key stakeholders with distinctive and complementary interests in clean energy access for cooking: (i) End-users, (ii) Energy Suppliers and (iii) Interest Groups in rural communities in Fiji, Ghana and Nigeria. The responses are analysed to conduct a comparative study across the three countries examined. Based on the above, an attempt is made to present broad base policy pathways for adopting clean cooking services in the rural community for sustainable development. The policy pathways harmonize the major stakeholders in the cooking space: Governments, Non-Governmental Organizations (NGOs), clean energy developers, business services and the end-users. In addition, a business model in the context of a rural community cooking space is proposed, stating that the initial life of the clean cooking business should be government-driven and, thereafter, followed by incentive-driven at the mid-life of the business (say, 25% technology penetration) and private-sector-driven at the late-life (say, 45% technology penetration). It is expected that the effort made in this work could be advanced by investigating the detailed techno-economic parameters of clean cooking technologies that could be influenced by the policy pathways established in connection with the sociocultural factors associated with energy services.

This work probes the dynamic co-movement between the Climate Policy Uncertainty Index (CPU) and the Renewable Energy and Clean Technology Index (RECT) employing the novel wavelet power spectrum (WPS) and wavelet coherence (WC) approaches for monthly data between 2013 and 2022. Using the wavelet approach enables us to observe the causality direction from both time and frequency dimensions and also to help detect the causal linkage in the short-medium and long-term horizons. This is the first study aiming to perform this relationship from both time and frequency dimensions. Remarkably, findings reveal that: i) CPU seems only volatile in 2019 and 2021 in the short run; (ii) there was significant volatility in the RECT in the short and long terms (SLT) between 2018 and 2022; (iii) RECT significantly caused the CPU between 2014 and 2018; iv) after 2019, CPU started to cause RECT in the short and medium terms (SMT).