Dünyada meydana gelen iklim krizi, enerji kaynaklarının azalması, insan kaynaklı çevresel bozulmalar, karbon emisyonu ve diğer zararlı gazlar hem insan yaşamını hem de diğer canlı türlerinin yaşamını olumsuz etkilemektedir. Bu zararı en aza indirmek ve sürdürülebilir yaşam koşullarını sağlamak için atmosfere zarar veren zararlı gazlardan karbon salınımını en aza indirmek için birtakım anlaşmalar ve düzenlemeler yapılmaktadır. Bu çalışmada, Bitcoin üretiminin karbon emisyonu üzerindeki etkisi incelenmektedir. Bu kapsamda, modele dahil edilen değişkenler arasındaki uzun ve kısa dönem ilişki 25 gelişmekte ve gelişmiş ülke için çeşitli ekonometrik yöntemler ile test edilmiştir. Çalışmada, bağımlı değişken olarak seçilmiş ülkelerin karbon emisyon değerleri, bağımsız değişkenler olarak ise, seçilmiş ülkelerin gayri safi milli hasılası, enerji tüketimi ve Bitcoin üretim verileri kullanılmıştır. Çalışmanın sonucunda, Bitcoin üretimi ile enerji tüketimi, gayrisafi milli hasıla ve karbondioksit emisyonu arasında uzun dönemli ve negatif bir ilişki tespit edilmiştir. Ayrıca, panel nedensellik test sonuçlarına göre, Bitcoin üretiminden karbon emisyonuna doğru tek yönlü bir nedensellik ilişkisi tespit edilmiştir. Bu çalışma, iklim değişikliği üzerine politika geliştiren politikacılar ve çevre üzerine çalışma yapan ilgili taraflar için önemli sonuçlar içermektedir.
Purpose The purpose of this study is to examine Bitcoin's price behavior across market conditions, focusing on the influence of Bitcoin's historical prices, news sentiment and market indicators like oil prices, gold and the S&P index. The authors also assess the stability of Bitcoin-inclusive hedging portfolios under different market conditions, for example, bearish, bullish and moderate market states. Design/methodology/approach This study uses the Quantile Autoregressive Distributed Lag model to explore the effects of different factors on Bitcoin's prices across various market situations. This method allows for a detailed analysis of historical trends, investor expectations and external market influences on Bitcoin's price movements and systematic stability. Findings Key findings reveal historical prices and investor expectations significantly influence Bitcoin in all market scenarios, with news sentiment exhibiting substantial volatility. This study indicates that oil prices have minimal impacts on Bitcoin, whereas gold is a stabilizing asset in bear markets, with the S&P index influencing short-term fluctuations. At the same time, Bitcoin's volatility varies with market conditions, proving more efficient as a hedging tool in bear and stable markets than in bull ones. Originality/value This study highlights the intrinsic correlation between Bitcoin's prices, news sentiment and financial market indicators, enhancing understanding of Bitcoin's market dynamics. The authors demonstrate Bitcoin's weak direct correlation with commodities like oil, the stabilizing role of gold in crypto portfolios and the stock market's indirect effect on Bitcoin prices. By examining these factors' impacts across various market conditions, the findings offer strategies for investors to improve hedging and portfolio management in cryptocurrency markets.
This study investigates the asymmetric impacts of Bitcoin prices on Bitcoin energy consumption. Two series are shown to be chaotic and non-linear using the BDS Independence test. To take into consideration this nonlinearity, we employed the QNARDL model as a traditional technique and Support Vector Machine (SVM) and eXtreme Gradient Boosting (XGBoost) as non-conventional approaches to study the link between Bitcoin energy usage and Bitcoin prices. Referring to QNARDL estimates, results show that the relationship between Bitcoin energy use and prices is asymmetric. Additionally, results demonstrate that changes in Bitcoin prices have a considerable effect, both short- and long-run, on energy consumption. As a result, any upsurge in the price of Bitcoin leads to an immediate boost in energy use. Furthermore, the short-term drop in Bitcoin values causes an increase in energy use. However, higher Bitcoin prices reduce energy use in the long run. Otherwise, every decline in Bitcoin prices leads to a long-term reduction in energy use. In addition, the performance metrics and convergence of the cost function provide evidence that the XGBoost model dominates the SVM model in terms of Bitcoin energy consumption forecasting. In addition, we analyze the effectiveness of several modeling approaches and discover that the XGBoost model (MSE: 0.52%; RMSE: 0.72 and R2: 96%) outperforms SVM (MSE: 4.89; RMSE: 2.21 and R2: 75%) in predicting. Results indicate that the forecast of Bitcoin energy consumption is more influenced by positive shocks to Bitcoin prices than negative shocks. This study gives insights into the policies that should be implemented, such as increasing the sustainable capacity, efficiency, and flexibility of mining operations, which would allow for the reduction of the negative impacts of Bitcoin price shocks on energy consumption.
Purpose Sustainable development hinges on a crucial shift to renewable energy, which is essential in the fight against global warming and climate change. This study explores the relationships between artificial intelligence (AI), fuel, green stocks, geopolitical risk, and Ethereum energy consumption (ETH) in an era of rapid technological advancement and growing environmental concerns. Design/methodology/approach This research stands at the forefront of interdisciplinary research and forges a path toward a comprehensive understanding of the intricate dynamics governing green sustainability investments. These objectives have been fulfilled by implementing the innovative quantile time-frequency connectedness approach in conjunction with geopolitical and climate considerations. Findings Our findings highlight coal market dominance and Ethereum energy consumption as critical short- and long-term market volatility sources. Additionally, geopolitical risks and Ethereum energy consumption significantly contribute to volatility. Long-term factors are the primary drivers of directional volatility spillover, impacting green stocks and energy assets over extended periods. Additionally, SHapley Additive exPlanations (SHAP) findings corroborate the quantile time-frequency connectedness outcomes. Research limitations/implications This study highlights the critical importance of transitioning to sustainable energy sources and embracing digital finance in fostering green sustainability investments, illuminating their roles in shaping market dynamics, influencing geopolitics and ensuring the long-term sustainability required to combat climate change effectively. Practical implications The study offers practical sustainability implications by informing green investment choices, strengthening risk management strategies, encouraging interdisciplinary cooperation and fostering digital finance innovations to promote sustainable practices. Originality/value The implementation of the quantile time-frequency connectedness approach, in line with considering geopolitical and climate factors, marks the originality of this paper. This approach allows for a dynamic analysis of connectedness across different distribution quantiles, providing a deeper understanding of variable interactions under varying market conditions.
Syed Muhammad Danish, Aroosa Hameed, Ali Ranjha, Gautam Srivastava · 5 authors
The increased charging demand resulting from the rapid development of electric vehicles (EVs) poses various challenges to the stable operation of the distribution network and smart grid. Due to the stochastic EV charging behaviour, the high charging demand at the charging stations (CSs) elevates the load curve which may lead to a spatially imbalanced load demand. As such, forecasting the highly stochastic EV charging load considering an individual EV's unique charging behaviour can result in maintaining the safe operation of the grid and distribution network. Therefore, in this work, we propose Block-FeDL, a blockchain-based Federated Learning (FL) approach for EV charging load forecasting considering the private and sensitive charging information of each EV user. Thereafter, we use a Bidirectional Long Short Term Memory (BiLSTM) model within the FeDL for predicting the EV charging load patterns at each client. Moreover, instead of using a centralized server for global model aggregation, we use blockchain technology, where the model aggregation is performed in a decentralized manner and the local model parameters shared by the FL clients can be validated and securely recorded. Lastly, the results show that the Block-FeDL outperform the second-best baseline method by 95%, 96% and 77% in terms of mean square error (MSE), mean absolute error (MAE), and root mean square error (RMSE) for forecasting the EV charging load.
Purpose This paper aims to investigate the effect of the economic policy uncertainty (EPU), geopolitical risk (GPR) and climate policy uncertainty (CPU) of USA on Bitcoin volatility from August 2010 to August 2022. Design/methodology/approach In this paper, the authors have adopted the empirical strategy of Yen and Cheng (2021), who modified volatility model of Wang and Yen (2019), and the authors use an OLS regression with Newey-West error term. Findings The results using OLS regression with Newey–West error term suggest that the cryptocurrency market could have hedge or safe-haven properties against EPU and geopolitical uncertainty. While the authors find that the CPU has a negative impact on the volatility of the bitcoin market. Hence, the authors expect climate and environmental changes, as well as indiscriminate energy consumption, to play a more important role in increasing Bitcoin price volatility, in the future. Originality/value This study has two implications. First, to the best of the authors’ knowledge, the study is the first to extend the discussion on the effect of dimensions of uncertainty on the volatility of Bitcoin. Second, in contrast to previous studies, this study can be considered as the first to examine the role of climate change in predicting the volatility of bitcoin. This paper contributes to the literature on volatility forecasting of cryptocurrency in two ways. First, the authors discuss volatility forecasting of Bitcoin using the effects of three dimensions of uncertainty of USA (EPU, GPR and CPU). Second, based on the empirical results, the authors show that cryptocurrency can be a good hedging tool against EPU and GPR risk. But the cryptocurrency cannot be a hedging tool against CPU risk, especially with the high risks and climatic changes that threaten the environment.
Abstract This paper extends the climate literature by examining the feasibility of integrating sub‐national governance into global club governance for mitigating CO 2 emissions. Global climate clubs become an argument for having separate bundles of emission targets and incentive mechanisms in the form of opportunities for climate finance and technology sharing among the club members. An exploratory analysis is important to examine the role of import and export taxes and other channels, such as the clean development mechanism, in meeting the objective of nonmember countries to join the club. The crux, however, is how, after determining national‐level quotas, the mitigation responsibilities are shared with subnational entities. We propose a design of a carbon entry tax at the subnational level, namely states, districts, and municipalities. The carbon entry tax uses the nighttime luminosity data published by NASA as a measure of carbon, which constitutes the tax base. The carbon entry tax serves as a fiscal instrument of decarbonization in a decentralized framework.
The visitor economy is responsible for a substantial percentage of the global carbon footprint. The mechanisms used to decarbonize it are insufficient, and the industry is relying on carbon trading with substandard credits that allow businesses to outsource the responsibility to decarbonize. We aim to transform carbon markets, help finance climate investments, and support decarbonization strategies. We identify and define the problem, outline the components and their interactions, and develop a conceptual model to transform carbon markets. The new, blockchain-based Carbon Tokenomics Model rolls out a decentralized database to store, trade, and manage carbon credits, with the goal of enabling sustainable climate finance investment. We outline the criteria needed for an industry-wide carbon calculator. We explain the process needed to increase rigor in climate investments in the visitor economy and introduce a delegated Proof of Commitment consensus mechanism. Our inclusive and transparent model illustrates how to reduce transaction costs and how to build consumer and industry trust, generating much-needed investments for decarbonization.
Jonas Yomboi, Mohammed Majeed, Esther Asiedu, Clement Nangpiire · 6 authors
As blockchain technology continues its disruptive influence across various sectors, its environmental implications have raised concerns about long-term viability and global repercussions. This chapter explores the concept of “green blockchain” as a framework for sustainable alternatives. It delves into the transition to energy-efficient consensus mechanisms like proof of stake. The chapter also addresses the regulatory landscape, ethical considerations, and future prospects, including the integration of artificial intelligence to optimize blockchain processes. Despite the potential benefits, challenges such as regulatory uncertainty, scalability concerns, and privacy risks underscore the industry's need to navigate carefully and strike a balance between innovation and environmental responsibility. The chapter advocates for a collective effort to build a culture of sustainability within the blockchain community and highlights successful community-led initiatives and regulatory frameworks as crucial elements in mitigating the environmental impact of blockchain technology.
He Peng, Yao Sun, Jianli Hao, Chunjiang An · 5 authors
Ground transportation, which includes the road and rail sectors, is a major source of greenhouse gas (GHG) emissions. An emissions trading system (ETS) is one of the environmental policies for controlling carbon emissions from fossil fuel combustion during transport activities. To investigate the status of existing ETS interventions on ground transportation emissions, a comprehensive literature review is conducted, including policy evaluation and comparison, scheme optimization and design, and specific transport behavior interventions. The results show that existing upstream policies are insufficient in stringency and effectiveness, while policy implementation for downstream interventions remains limited. To address these shortcomings, this study proposes a downstream ground transportation emissions trading system (GTETS), incorporating the Internet of Things and blockchain technology. As well as road and rail transportation emissions, the system includes the emissions-related activities of individuals and transportation companies, and its Web3-based technologies provide effective and efficient monitoring, reporting, and verification.
The significant release of carbon dioxide into the atmosphere poses substantial threats to both global ecosystems and human well-being. Among the primary sources of these emissions, the transportation sector emerges as a crucial contributor. There exists a direct and notable link between CO2 emissions and transportation, with this industry being a major emitter of greenhouse gases, and CO2 acting as the primary catalyst for global climate change. Additionally, the swift spread of cryptocurrencies, coupled with increasing dependence on advanced technologies and the quick pace of technological advancements, poses ongoing challenges, especially concerning environmental sustainability and carbon emissions. This research explores the tangible effects of Bitcoin transaction volumes and their energy usage on environmental sustainability. The findings reveal a strong link between CO2 emissions and Bitcoin transactions, showing a complex relationship between public awareness of environmental problems related to Bitcoin transactions. The study confirms that energy use positively influences CO2 emissions both in the short and long term.
Thobekile Qabhobho, Cwayita Mpuku, Izunna Anyikwa, Andrew Phiri
since the onset of the cOViD-19 pandemic, african currencies, cryptocurrencies, and commodity markets have undergone significant fluctuations, displaying fat-tail properties that lies at the outer ends of the normal probability curve.the recent Russia-Ukraine war has further disrupted these markets, generating considerable interest among academics and practitioners.Our study delves into tail-end returns and volatility connectedness between Bitcoin, crude oil, gold, and four african currencies amidst the cOViD-19 and Russia-Ukraine war.employing a quantile vector autoregressive (QVaR) approach, we analyze tail-end spillover effects between markets from 4 november 2019, to 7 september 2022.Our findings reveal heightened connectedness at the quantile ends of co-movements, with left-tail spillovers being more pronounced for returns, while right-tail spillovers dominate for volatility.Bitcoin, and to a lesser extent gold and oil, emerge as effective tail-ended hedges for the egyptian Pound and nigerian naira but not for other african currencies like the algerian Dinar and south african Rand.consequently, users of egyptian and nigerian currencies in international financial markets can seek hedging opportunities in traditional cryptocurrencies and commodities during recent Black swan events, unlike those using south african and algerian currencies.additionally, our results suggest limited diversification benefits associated with (i) currencies linked to oil-exporting or oil-importing countries, (ii) currencies linked to shariah-compliant financial systems, but do indicate diversification benefits in high-inflation environments.these findings hold relevance for investors seeking improved hedging strategies against african currency risk and for african policymakers aiming to enhance intra-continental trade, foreign direct investment, and cross-border business expansions.
We analyze the hedging feature of gold against inflation by analyzing the factors affecting gold prices for the post-2013 period, including the tapering process in the United States. Our results show that especially demand for gold Exchange Traded Funds (ETFs) and US 10-year bond rates are effective on gold prices in this period. Inflation has no statistically significant effect on gold prices over the sample period; however, in the subperiod, excluding 2014–2019, inflation has a statistically significant positive impact on gold prices. We conclude that gold does provide a partial hedge against inflation as an investment tool, at least for the recent period. Furthermore, our analysis of Bitcoin’s effect on gold prices starting in the second half of 2016 shows no statistically significant relationship.
In recent years, utilization of distributed generation systems has been announced as a strategic and tactical mission of Iran’s Ministry of Energy (IME) to supply electricity. Successful implementation of this mission needs to investigate the energy buying regulations and technical and financial considerations in the distribution processes. On the other hand, the development of blockchain technology as a safe and transparent platform for conducting financial transactions as well as providing smart contracts has been widely established in the last decade. Therefore, this paper tries to propose a conceptual framework to manage the electricity trade with Distributed Generation (DG) systems using the smart contract platform. Furthermore, the interactions between network members are discussed in detail.
This paper investigates the evolving landscape of blockchain technology in renewable energy. The study, based on a Scopus database search on 21 February 2024, reveals a growing trend in scholarly output, predominantly in engineering, energy, and computer science. The diverse range of source types and global contributions, led by China, reflects the interdisciplinary nature of this field. This comprehensive review delves into 33 research papers, examining the integration of blockchain in renewable energy systems, encompassing decentralized power dispatching, certificate trading, alternative energy selection, and management in applications like intelligent transportation systems and microgrids. The papers employ theoretical concepts such as decentralized power dispatching models and permissioned blockchains, utilizing methodologies involving advanced algorithms, consensus mechanisms, and smart contracts to enhance efficiency, security, and transparency. The findings suggest that blockchain integration can reduce costs, increase renewable source utilization, and optimize energy management. Despite these advantages, challenges including uncertainties, privacy concerns, scalability issues, and energy consumption are identified, alongside legal and regulatory compliance and market acceptance hurdles. Overcoming resistance to change and building trust in blockchain-based systems are crucial for successful adoption, emphasizing the need for collaborative efforts among industry stakeholders, regulators, and technology developers to unlock the full potential of blockchains in renewable energy integration.
Renewable energy trading could be considered the next step in power trading's development. It is probable that individuals currently involved in power trading will need to upgrade their data collection, processing, and reporting systems. This article provides a comprehensive evaluation of renewable energy trading utilizing Blockchain technology. Initially, the paper examines country-specific renewable energy trading with a focus on India, China, the US, France, and Germany's renewable energy policies. Moreover, the paper presents potential renewable energy trading markets such as peer-to-peer, over the grid, and partially or fully independent microgrid's. This paper shows the appraisal of bond, commodity, derivative, and algorithm-based renewable energy trading using different Blockchain methods, including Ethereum and R3 Corda. It is find out during the renewable energy trading, proposers of bid, also include capital cost of the renewable energy power plant, salvage value after useful life of different component of renewable energy power plant. It is also find out proper trading is to be done with offering subsidies of up to 70% of the capital cost, and with a 30% viability gap finance (VGF) at this cost.
Oktay Özkan, Salah Abosedra, Arshian Sharif, Andrew Adewale Alola
Abstract The objective of this paper is to assess the dynamic volatility connectedness between fossil energy, clean energy, and major assets i.e., Bonds, Bitcoin, Dollar index, Gold, and Standard and Poor's 500 from September 17, 2014 to October 11, 2022. The main motivation of the study relates to examining the dynamic volatility connectedness mentioned during periods of important events such as the recent coronavirus pandemic and the Russia–Ukraine conflict which has shown the vulnerability of economic and financial assets, energy commodities, and clean energy. The novel Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) approach is employed for the investigation of the sample period mentioned. Empirical analysis reveals that both the total and net volatility connectedness between assets is time-varying. The highest connectedness among the assets is observed with the onset of the coronavirus (COVID-19) pandemic, and it increases with some important international events, such as the Russia–Ukraine conflict, the referendum of Brexit, China–US trade war, and Brexit day. On average, the result shows that 32.8% of the volatility in one asset spills over to all other assets. The DCC-GARCH results also indicate that crude oil, bonds, and Bitcoin act as almost pure volatility transmitters, whereas the Dollar index, gold, and S&P500 act as volatility receivers. On the other hand, clean energy is found neutral to external shocks until the first quarter of 2020 and after that time, it starts to behave as a volatility transmitter. Based on the obtained results, we offer some specific policy implications that are beneficial to the US economy and other countries. Graphical Abstract Dynamic volatility connectedness between fossil energy, clean energy, and major assets (Bonds, Bitcoin, Dollar index, Gold, and Standard and Poor's 500)