Blockchain Papers

Aaron Zimba, Katongo Ongani Phiri, Mwenge Mulenga, George Mukupa

No abstract is available for this record.

Shubham Gupta, Kusumakumari Vanteru, Srinivas Reddy, Bhanuprakash Madupati

Climate change is the most pressing global problem, which warrants technological innovation in accurate monitoring and efficient market-based solutions. In this paper, we propose a framework to combine staking with artificial intelligence and blockchain to provide a transparent, secure, and efficient way of monitoring a variety of carbon credits related to carbon footprint. This uses machine learning algorithms to combine satellite imagery, IoT (wearable) data, and immutable blockchain ledgers to create tamper-proof environmental monitoring systems. It suggests brilliant contract architecture that can generate carbon credits through AI to validate the process, federated learning applications to track cross-border emission activity, and neural networks to validate carbon sequestration projects. Using these systems, we achieved orders of magnitude improvement in verification accuracy, transaction transparency, and market efficiency over traditional systems. By employing this integrated approach, some of the most pressing carbon market dilemmas, including narrowing carbon market data integrity issues, delays in verification, and deficits of trust among carbon market participants, can be resolved, and it is a strong foundation for climate action globally.

Bama Raja Segaran, Siti Nurulain Mohd Rum, Mohd Izuan Hafez Ninggal, Teh Noranis Mohd Aris

Abstract The rapid growth of carbon credit markets, driven by global efforts to mitigate climate change, highlights the critical need for transparency and accountability—particularly in forest-based carbon offset projects. Forest ecosystems play a vital role in carbon sequestration; however, these projects are increasingly vulnerable to greenwashing, where organizations exaggerate or misrepresent their environmental impact to appear more sustainable than they are. This literature review explores the integration of blockchain technology and machine learning (ML) to enhance verification processes and reduce fraudulent practices in forest carbon credits. Blockchain’s decentralized, immutable ledger offers a transparent and tamper-proof system for recording carbon credit transactions, ensuring traceability and reducing the risk of manipulation. Smart contracts embedded within blockchain networks can automate verification and compliance processes, enhancing efficiency while minimizing the need for human oversight. However, while blockchain ensures transparency, it lacks real-time anomaly detection capabilities. ML algorithms, particularly supervised models such as Random Forest, XGBoost, and Neural Networks, are well-suited for detecting fraudulent patterns and verifying the authenticity of forest carbon credit transactions. These algorithms can process large datasets, including satellite imagery and corporate disclosures, to identify discrepancies and improve the accuracy of carbon sequestration claims. This review also examines key performance metrics such as accuracy, precision, recall, and processing time to evaluate the efficiency of various ML algorithms for real-time fraud detection. The findings suggest that integrating ML and blockchain technologies, combined with satellite data, can significantly strengthen transparency and verification in forest carbon credit markets. By enhancing verification mechanisms, this interdisciplinary approach helps mitigate greenwashing and fosters a more credible and transparent carbon credit market. It supports global sustainability efforts by ensuring that carbon sequestration claims from forest-based projects are both accurate and verifiable.

Ali Çeli̇k, Metehan Özırmak

ABSTRACT Assuring environmental sustainability is essential for the continuity of the ecosystem. Every sector of the economy has some degree of impact on environmental sustainability. The United Nations (UN)’ Sustainable Development Goals (SDGs) have placed these objectives within a broader global framework, offering a global plan aimed at ensuring environmental sustainability. This study assesses the role of cryptocurrency mining on environmental sustainability, incorporating monthly data for the period from 2015 to 2023. In this context, the impact of the electrical energy consumed in Bitcoin mining, which has the largest transaction volume among cryptocurrencies, and the climate policy uncertainty on Bitcoin greenhouse gas (GHG) emissions are examined by applying dynamic stimulated autoregressive distributed lag (DARDL) and kernel‐based regularized least squares (KRLS) methods. The results of the empirical analysis indicate that the increase in Bitcoin electricity consumption and climate policy uncertainty have a significant negative impact on Bitcoin GHG emissions. Put another way, cryptocurrency mined using fossil fuels and climate policy uncertainty poses a considerable threat to environmental sustainability. These findings are crucial for policy makers and all stakeholders who want to achieve environmental sustainability goals to develop proactive proposals. It is also highlighted that Bitcoin mining should bring environmental regulations that can mitigate environmental degradation.

Sid-Ali Amamra

This research presents an innovative blockchain-based solution for the charging and energy trading of electric vehicles (EVs). By combining the strengths of two prominent consensus mechanisms, Proof of Work (PoW) and Proof of Stake (PoS), the proposed system balances security, decentralization, and energy efficiency. PoW secures the blockchain, while PoS enhances energy efficiency and scalability, key factors in meeting the growing demand for EV infrastructure. The system’s decentralized nature allows for EV owners, charging stations, and stakeholders to interact and transact transparently, without relying on centralized entities. The research conducts a comprehensive simulation to assess the performance of the proposed hybrid blockchain model, demonstrating significant improvements in cost-effectiveness, scalability, and energy management. Additionally, dynamic pricing mechanisms within the blockchain enable real-time energy trading, optimizing charging times and balancing grid demand efficiently. Through the use of smart contracts, automated pricing adjustments, and incentive-driven user behaviors, the proposed system paves the way for more sustainable, cost-effective, and efficient energy solutions in the future.

Matin Farhoumandi, Sheida Bahramirad, Mohammad Shahidehpour, Ahmed Alabdulwahab

ABSTRACT The proliferation of distributed energy resources (DERs) and the large‐scale electrification of transportation are driving forces behind the ongoing evolution for transforming traditionally passive consumers into prosumers (both consumers and producers) in coordinated power distribution network (PDN) and urban transportation network (UTN). In this new paradigm, peer‐to‐peer (P2P) energy trading is a promising energy management strategy for dynamically balancing the supply and demand in electricity markets. In this paper, we propose the application of Blockchain (BC) to electric vehicle charging station (EVCS) operations to optimally transact energy in a hierarchical P2P framework. In the proposed framework, a decentralised privacy‐preserving clearing mechanism is implemented in the transactive energy market (TEM) in which BC's smart contracts are applied in a coordinated PDN and UTN operation. The effectiveness of the proposed TEM and its solution approach are validated via numerical simulations which are performed on a modified IEEE 123‐bus PDN and a modified Sioux Falls UTN.

Oliver O. Apeh, Nnamdi Nwulu

• Blockchain can be used to create token-based inducement systems. • The integration of blockchain supports distributed energy systems and P2P in green energy trading. • Blockchain technology allows transparent and immutable recording of green energy transactions. • Blockchain facilitates automated and efficient trading of renewable energy. • Key trends and influential papers in the field are identified using bibliometric analysis. Blockchain is evolving as a crucial technology in protecting the future outlook of energy systems and global economic competition. As a result of the huge rise in industrial pollution, it has gained extensive consideration from economic establishments, green energy supply organizations, tech designers, governments, and researchers. Stakeholders from various fields identify the potential of blockchain integration with green energy as a tool to transform different activities in the sector, such as reducing the grid's major carbon emissions, freeing cyber theft and generating novelty. Moreover, blockchain system is tamper-proof, transparent, and has the prospect of addressing novel business solutions, mostly when integrated with smart contracts. In this study, 510 documents from 2017 to 2024 were selected and visualized using CiteSpace software and bibliometric approaches to analyze the research field's growth base, hotspot areas, country and their policy implementations, collaborative groups, and evolutionary trends of blockchain base within energy networks. It investigates the existing literature to acknowledge the progress made in the field. The key findings show that basic research on blockchain technology in the energy sector is fast growing with time, showing that integrating blockchain and green energy is an emerging research field. Out of 742 countries and regions, China leads with 89 publications, recording 24.7%, followed by India with 78 publications, accounting for 21.7%, and the United States with 76 publications, accounting for 21.1%. Among them, China's collaborations rely mainly on renewable energy management. Moreover, the practical application cases corresponding to research hotspots are mostly located in developed countries, especially in the United States, the European Union, and Australia. The research gaps in blockchain-based green energy applications are noticed in green certificate trading, micro-grid energy market, technology and policy, energy management, as well as potential trends in energy internet, energy systems, and green power trading. The findings of this paper will assist researchers in gaining a vast knowledge of the present research in the area of blockchain and green energy and identify future research trends in the field. Hence, this will boost the knowledge of energy expansion among energy trading experts, seize possible opportunities, and offer beneficial insights for the government to introduce blockchain advancement and green energy trading policies.

Magdalena Rãdulescu, Kamel Si Mohammed, Abdelmohsen A. Nassani, Nicoleta Dascalu

This study investigates the impact of Bitcoin's energy and water consumption on environmental sustainability, focusing on the load capacity factor (LCF) and the roles of energy transition green technology in major cryptocurrency-producing nations. Utilizing the method of moments quantile regression (MMQR) approach, the findings reveal a negative impact of mining energy consumption on environmental sustainability, particularly in the lower quantiles, with a stronger negative effect in the higher quantiles. Energy transition plays a critical role in moderating this impact, though the shift towards cleaner energy sources has not been sufficient to mitigate the adverse environmental effects. The water footprint has limited influence on LCF across upper and lower quantiles. Moreover, the results do not support the LCF hypothesis. An increase in mining activity leads to a rise in LCF, while this effect turns negative in the 90th quantile. These findings underscore the importance of energy transition in reducing Bitcoin's environmental footprint and emphasize the need for policymakers to swiftly enact regulations and foster innovative technologies to promote environmentally sustainable digital currencies while providing valuable insights into water resource management.

Chung-Chi Hsieh, C.H. Wu, Artya Lathifah

As consumer demand for eco-friendly products continues to grow, manufacturers are increasingly driven to enhance product greenness and disclose this information. Blockchain technology emerges as a pivotal enabler, facilitating credible communication of manufacturers’ sustainability efforts to consumers through retail platforms and influencing supply chain decisions concerning sustainability, pricing , and blockchain adoption. While existing research has extensively examined the positive moderating effect of blockchain technology on consumers’ perceived value of product greenness in retail competition or green supply chain contexts, there remains a significant gap regarding its cross-channel influence in situations of information disclosure asymmetry across retail platforms. To address this gap, we investigate the interactive dynamics of a green supply chain under asymmetric platform competition, where the incumbent platform offers blockchain services while the new platform does not. Our findings indicate that the manufacturer’s decision to adopt blockchain depends significantly on market conditions. Notably, the manufacturer’s inclination towards blockchain adoption widens for a broader range of blockchain costs when the cross-channel influence is pronounced. Moreover, the alignment of the manufacturer’s blockchain adoption strategy with the incumbent platform’s preference is not guaranteed. In scenarios where their interests diverge, joint efforts to reduce blockchain costs can be a viable strategy. Our parametric analysis further reveals that while the cross-channel influence contributes positively to enhancing product greenness and the manufacturer’s profit, it could diminish the profits of both platforms under certain conditions.

Zhiyi Yang

This study explores the feasibility of Bitcoin as a legal currency and a store of value in comparison to traditional fiat currencies. Through a comprehensive literature review and discussion, the study examines Bitcoin’s core characteristics such as circulation limitations, scarcity, price stability, intrinsic value, and associated security risks. The analysis highlights key challenges, including Bitcoin’s limited acceptance in global commerce, high volatility, and the potential risks posed by its decentralized nature. While Bitcoin’s scarcity and technological innovation position it as a unique asset, its viability as a mainstream currency remains uncertain due to its lack of regulatory support and price stability. The paper concludes that although Bitcoin holds promise as a digital asset, it faces significant obstacles in replacing fiat currencies as a stable medium of exchange or a reliable store of value. Recommendations are provided for governments and institutions on regulatory approaches and the integration of cryptocurrencies into the existing financial system.

Akshat Miglani, Khush Patel, Margesh Modi, Yana Gadhvi · 5 authors

As a theoretical foundation and overview, the paper explains how blockchain technology influences energy trade and finance through decentralized, safe, and transparent peer-to-peer transactions. It examines the current energy crisis that arises with a steep, rising curve of rather unorthodox consumption of energy and calls for cleaner, more reliable sources of energy. It also discusses how blockchain-based platforms could help eliminate persistent challenges in centralized energy systems. By combining the previous literature on distributed ledgers, smart contracts, and decentralized market mechanisms, we find that blockchain provides faster settlements, lower overheads, and enhanced resilience against single points of failure. This study will review how blockchain-enabled energy finance solutions speed transactions, build trust, and allow for innovative funding approaches, such as green bonds and energy banking. All in all, the findings support blockchain as a viable way of achieving a more flexible, customer-oriented, and environmentally sustainable energy sector while showcasing the technological, regulatory, and operational gaps that research and responsible policy actions must address. • Examines Blockchain's decentralized role in energy trade and finance. • Explores Blockchain's advantages and challenges in energy finance integration. • Reviews Blockchain models for platform, tech, privacy, and security solutions. • Highlights Blockchain's potential to enable trust and direct energy transactions. • Discusses future needs for advanced algorithms and supportive regulations.

Yasmine Snene Manzli, Mohamed Fakhfekh, Azza Béjaoui, Hind Alnafisah · 5 authors

This paper investigates the diversification, hedging, and safe-haven capabilities of Bitcoin and gold against blue economy and green finance assets using three different MGARCH models (DCC, ADCC, and GO-GARCH) during adverse events such as the COVID-19 health crisis and the 2022 Russia-Ukraine conflict. Blue economy assets, which refer to sectors that sustainably utilize ocean resources, are a key focus alongside green finance assets. The findings reveal that during crises, Bitcoin demonstrates robust safe-haven characteristics, particularly against blue economy assets like BJLE and OCEN. Conversely, gold exhibits pronounced safe-haven properties against specific blue economy and green finance assets such as BJLE and FAN. The GO-GARCH model highlights gold's strong diversification and safe-haven roles, especially against BJLE. Bitcoin, on the other hand, is more effective as a diversifier for PIO. Moreover, the GO-GARCH model consistently outperforms the DCC and ADCC models in terms of hedging effectiveness, showing that gold is the preferred hedging instrument for GNR and TAN, while Bitcoin is more effective for other blue and green assets. The results underscore the distinct roles of Bitcoin and gold in portfolio management strategies, offering insights for investors navigating market uncertainties in the context of sustainable investments.

Asysta Amalia Pasaribu

Investment is an activity that is popular nowadays. Profitable investments are the hope of every investor. By investing. investors expect the invested assets to generate returns and to obtain profits for future life In investment studies. the most frequently discussed topic is the fluctuations. whether increases or decreases. of an asset's price (stocks). The risk of investment is loss in financial. The fluctuations of stock prices represent risks in the investment field. One measure used to determine gains and losses from stock prices is the return. To know return from data. we may use the compound return formula. Returns have empirical facts that require several tests. In this study. the empirical facts of returns are that the returns are not autocorrelated (autocorrelation function) and that the returns are leptokurtic distributed (thick-tailed distribution). We use the price data of Bitcoin (BTC) and Gasoline (UGA) from January 1. 2019. to December 31. 2023. The main of purpose of this research is to show empirical analysis of the Bitcoin and Gasoline return data. The results of the empirical analysis show that the return of stock price for Bitcoin (BTC) and Gasoline (UGA) meet the empirical properties of returns so that they can capture a good volatility model.

Murray A. Rudd, Dennis Porter

We develop a flexible supply and demand equilibrium framework that can be used to develop pricing models to forecast Bitcoin’s price trajectory based on its fixed, inelastic supply and evolving demand dynamics. This approach integrates Bitcoin’s unique monetary attributes with demand drivers such as institutional adoption and long-term holding patterns. Using the April 2024 halving as a baseline, we explore model scenarios with varying assumptions about growth in adoption and supply-side constraints, calibrated to real-world data. Our findings indicate that institutional and sovereign accumulation can significantly influence price trajectories, with increasing demand intensifying the impact of Bitcoin’s constrained liquidity. Forecasts suggest that modest withdrawals from liquid supply to strategic reserves could lead to substantial price appreciation over the medium term, while higher withdrawal levels may induce volatility due to supply scarcity. These results highlight Bitcoin’s potential as a long-term investment and underline the importance of integrating economic fundamentals into forward-looking portfolio strategies. Our framework provides flexibility for testing different market scenarios, demand curve functional forms, and parameterizations, offering a tool for investors and policymakers considering Bitcoin’s role as a strategic asset. By advancing a fundamentals-based approach, this study contributes to the broader understanding of how Bitcoin’s supply–demand dynamics influence market behavior.

Indri Haryani, Indra Ardhanayudha Aditya, Almareta Harasti Nuraini, Sri Widiyanesti · 10 authors

The renewable Energy Certificate (REC) schemes play a crucial role in combating climate change and promoting sustainable living. However, issues such as traceability, lack of transparency, and user awareness limit its effectiveness. The current study aims to address such limitation by proposing a blockchain-based solution for Indonesia's electricity grid which can enhance end-to-end traceability, real-time data access, and tamper-proof records. The methodology encompasses interview with energy stakeholders, blockchain model development, prototyping, and evaluation of its efficacy. Results show that blockchain technology can revolutionize Indonesian REC market by improving security, traceability, and promote stakeholders' trust. The proposed framework addresses current system limitation and introduces a semi-fungible REC token for secure issuance, trading, and verification. Our solution offers a scalable model that can support Indonesia and global green energy adoption and sustainable living.

Benjamin Walwai Miba’am, H. Yusuf GÜNGÖR

Abstract The study attempts to add to the existing literature on the relationship between uncertainties and Bitcoin by determining the direction of the relationship between Economic Policy Uncertainty (EPU), Geopolitical Risk (GPR), Political Risk (PR) and Bitcoin returns. This is to ascertain if Bitcoin hedges and is a safe haven asset against uncertainties. We employed the use of Ordinary Least Square (OLS), Autoregressive Distributive Lag (ARDL) and Quantile Regression (QR) to achieve the research objective. Having discovered the existence of structural breaks after conducting the Zivot-Andrews unit root for structural breaks, the analysis was divided into full sample period, first sub-period and the second sub-period. Findings show that EPU, GPR and PR hedge and play the role of safe haven against uncertainties in the United States (US). We found that EPU exerts positive influence against Bitcoin returns while GPR and PR negatively influence Bitcoin returns. The result further shows that Bitcoin returns hedges against EPU in the lower and middle quantiles while Bitcoin returns hedges against PR only in the lower quantile. The study therefore concludes that uncertainty and risk in the US influence bitcoin returns. It supports the hedging ability and safe haven properties of bitcoin, emphasising that bitcoin returns react more to EPU US than GPR US and PR US, therefore recommending investment experts and financial analysts focus more on EPU US than GPR US and PR US.

Brian wakasala

Abstract: This systematic review of literature bears the objective of exploring the potential of transformative novel blockchain technology, its regulation, and the substantive impact it bears on renewable energy firms' competitive advantage. The study provides a minutiae of the current trends in research, their implications, and blockchain implementation and innovation between 2019 to 2024. The methodology comprised a comprehensive search of scholarly databases, selection, and analysis of the relevant research studies. The findings revealed that Blockchain is essential based on its transparency, traceability, data privacy, and decentralization features which enhance trust, transparency, and traceability across the supply chain. Furthermore, blockchain technology is relevant in the renewable energy sector in Kenya ranging from p2p trading platforms, digitization by IoT, E-mobility, and decentralized trading platforms. The distributed ledger technology is a promising disruption for a wide area of service and product management in the energy sector ranging from the producers, transmitters, regulators, and distributors involved. The review concludes with future research recommendations and the practical implications for the industry players and the regulators.

S. S. Tyagi

The cryptocurrency market, known for its high volatility and immense data availability, provides an excellent opportunity for predictive modeling. This paper explores the prediction of Ethereum’s price using four distinct models: Random Forest, Logistic Regression, Long Short-Term Memory Networks (LSTM), and CNN-LSTM hybrid models. The study evaluates the performance of these models based on metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Rsquared ( R2 ), and Accuracy (%). The findings highlight that Logistic Regression outperformed the other models with the lowest MSE (6741.12) and highest accuracy (98.66% ) [Table 1]. This research demonstrates the potential of combining traditional and advanced machine learning techniques to achieve robust price prediction in the cryptocurrency domain.

Pratyush Kumar Patro, Raja Jayaraman, Adolf Acquaye, Khaled Salah · 5 authors

The aviation industry's carbon emissions are forecast to rise to 22% by 2050, posing a significant challenge to the goal of achieving Net Zero Emissions by the same year. Regardless of the structural or agentic strategies implemented to reduce these emissions, ensuring effective traceability of emissions in airline operations is crucial, as it enables the development of effective mitigation measures. Existing systems fall short of effectively providing end-to-end traceability of emissions within an effective carbon accounting framework. Indirect emissions and the complexities associated with emissions tracking throughout the extended aviation sector also exacerbate carbon accounting and offsetting difficulties. In this paper, we present a blockchain-based framework to address these plausible challenges. The proposed work categorises both direct and indirect emissions under Scope 1, 2, and 3 classifications. A blockchain-based collaborative platform, also provides data transparency across all stakeholders, ensuring traceability and security in a decentralised and reliable manner. A prototype model of a blockchain-based system is therefore developed using Ethereum smart contracts. The paper presents a cost and security analysis of the system, while highlighting the challenges and opportunities for the development of sustainable aviation operations. The smart contract is made publicly available on Github for verification.

Yun‐Cheng Tsai

Net-zero emission targets require transparent and efficient carbon credit trading systems. This paper introduces a blockchain-based data visualization framework to enhance decision-making in the production and logistics sectors by simplifying blockchain transaction records and identifying potential arbitrage activities. The framework integrates real-time decision support tools, enabling production system managers to monitor carbon offset activities, detect fraudulent behaviors, and streamline operations. This research provides actionable insights into supply chain emissions management and operational risk reduction by leveraging advanced visualization techniques. The proposed approach offers innovative solutions to address the complexities of blockchain-based carbon trading, emphasizing transparency and sustainability. Our analysis demonstrates the effectiveness of these techniques in mitigating fraud and supporting compliance with international carbon trading standards. The findings contribute to integrating advanced technologies into sustainable production systems, offering practical implications for achieving global climate change mitigation goals and fostering a more efficient and secure carbon credit market.

Vittorio Capocasale, Maria Elena Bruni, Guido Perboli

Purpose Blockchain and distributed ledger technologies are increasingly prominent, yet their adoption remains complex. This paper addresses the common misalignment between blockchain technology and actual needs, often leading to project failure. It introduces a decision-making framework focused on the technological aspects of blockchain adoption. Design/methodology/approach We designed the framework by analyzing key decision drivers from existing literature and applied it to a real-world use case in the electric vehicle supply chain. The blockchain solution was tested with live production data. Findings Blockchain is beneficial for use cases requiring decentralized governance, but it often needs to be supplemented with additional technologies in industrial applications. Originality/value The framework provides a set of managerial-level questions that simplify the decision-making process for those without deep technical expertise, helping determine when blockchain is appropriate, valuable and superior to other technologies.

B J Santiyano, V F Tanty, J Hariwinarta, Shinta Amalina Hazrati Havidz

Abstract This study investigated the effects of macroeconomic and environmental factors on Bitcoin return. The analysis included 31 lower-income countries selected based on their GDP rankings from 2012 to 2022. Using 341 observations, we applied Feasible Generalized Least Squares (FGLS) and One-step System Generalized Method of Moments (GMM) to evaluate the effects of Gross Domestic Product (GDP), Inflation Rate (INF), CO2 Emissions (CO2E), Climate Policy Uncertainty (CPU), Global Price Energy Index (GPEI), and Cambridge Bitcoin Electricity Consumption Index (CBECI) on Bitcoin return. The findings revealed a significant negative relationship between CO2E and Bitcoin return, reflecting investor concerns about Bitcoin’s environmental impact. CBECI showed a significant positive effect, suggesting that higher electricity consumption associated with mining activities led to increased Bitcoin return. CPU was positively associated with Bitcoin return, indicating that investors might have viewed Bitcoin as a hedge against climate policy uncertainties. GPEI had a significant negative effect, demonstrating Bitcoin’s sensitivity to global energy price fluctuations. GDP and INF showed no significant effect on Bitcoin return, suggesting that macroeconomic indicators did not significantly impact Bitcoin’s value in emerging markets. These results offered essential guidance for investors and policymakers in emerging markets.

Zhenxin Ren

No abstract is available for this record.

Janardhana Anjanappa

No abstract is available for this record.