Mohammadhossein Lashkaripour, Seyed Mehdi Hosseini, Rizwan Ahmed
Bitcoin contributes to global carbon emissions on a scale comparable to entire countries in order to secure its decentralized network. This exposes Bitcoin to climate policies aimed at reducing emissions. This paper develops a general equilibrium framework to examine how the stringency of climate policy affects Bitcoinâs valuation and its relationship with the equity market. Our theoretical analysis delivers a key insight: a transition from a lenient to a stringent climate policy increases the conditional correlation between Bitcoin and equity returns, thereby compromising Bitcoinâs appeal as a hedge or diversifier against equity market volatility. Empirical evidence supports this theoretical prediction.
Taegyum Kim, Hyeontae Jo, Woohyuk Choi, BongâGyu Jang
ABSTRACT This paper aims to improve Bitcoin price direction prediction using a CNNâLSTM model that incorporates various relevant indicators, such as stock market indices, commodity indices, and interest rates. Separate models are trained for predicting price up and down direction and combined to enhance prediction accuracy. We utilize binary classification models to independently analyze the impact of different features, verified through explainable artificial intelligence techniques. Additionally, an investment strategy based on our model is proposed and compared with traditional strategies, specifically focusing on maximum drawdown relative to the S&P500 buyâandâhold strategy. Results suggest that our strategy offers potential for stable investment in Bitcoin, showcasing its value as a financial asset. This study demonstrates the role of deep learning in Bitcoin price direction prediction and investment strategy development and contributes to future research on cryptocurrency forecasting and investment approaches.
Addressing the shortcomings of the Voluntary Carbon Markets (VCMs), a nascent blockchain industry has disrupted this area with an ever-growing number of projects leveraging open-source, decentralised base-layer platforms (e.g. Ethereum, Cosmos) and business-oriented decentralized applications (Dapps). Building on this emerging digital infrastructure over the Internet, community-driven decentralized autonomous organizations (DAOs) are building new socio-technical systems for decentralized finance (DeFi) and, more recently, regenerative finance (ReFi). Both areas are making their way into VCMs promising improved transparency, efficiency and greater accessibility. This paper examines the goals, scope, and intended outcomes of prominent blockchain-based ReFi projects in the VCM space. In particular, it explores the potential for commons-based outcomes emerging from peer-to-peer configurations in the VCM. Using a qualitative approach, the study analyses text-data from industry whitepapers focusing on the cases of Celo, Regen, Toucan, Klima and Moss. The findings show the ReFi ecosystem as a low-transaction-cost environment fostering open-source prototypes of peer-production for carbon accounting and trading. These innovations materialize through application interfaces operating on base-layer blockchains running smart-contracts and tokens. The tokenization of real-world assets (RWA) or rights (e.g. renewable energy generation, storage capacity, or forestry land) and the automation of operations (e.g. exchanges) via smart contracting, provides participants with new affordances for secure, bi-directional coordination in near-real time. The preliminary conclusion is that, while the ReFi organizations considered seem to be Ostrom-compliant with regard to some principles (e.g. clearly defined boundaries, procedures for making own rules, monitoring, or minimal recognition of rights) others are still ad-hoc practices or work in progress (e.g. graduated sanctions or dispute resolution mechanisms). This study contributes to the critical exploration of enhanced governance mechanisms, enabled by technological innovation, that can address climate action challenges and provide viable alternatives to traditional market-based approaches.
This study examines the influence of cryptocurrency's environmental footprint on market behavior through an analysis of 66,582 Reddit posts about Bitcoin and 23,231 about Ethereum. Using a vector autoregression (VAR) model, it explores the relationship between social media discussions on environmental issues, electricity use, and cryptocurrencies' market dynamics. We find a negative correlation between environmental discussions and Bitcoin volatility. Moreover, real electricity use has a more pronounced impact than social media discussions on both Bitcoin and Ethereum volatility. This indicates that crypto market investors prioritize real-world indicators over information from social media discussions. The study also reveals a bidirectional relationship between Bitcoin volatility and environmental posts, highlighting the complex interplay between market behavior and public discourse on environmental matters in the cryptocurrency domain. These results suggest the need for policies that limit energy consumption due to mining, promote renewable energy, and enhance investor education on environmental impacts to support sustainable practices in the cryptocurrency market.
Madhusudan Naik, Akhilendra Pratap Singh, Nihar Ranjan Pradhan, Abdullah M. Almuhaideb · 5 authors
Electric vehicle (EV) charging stations (CSs) are increasingly prevalent due to the growing adoption of renewable energy. Solar CSsâ main difficulties are energy efficiency, security, traceability, and sustainability. This article presents a novel blockchain-enabled EV charging framework that addresses these challenges using the Ethereum virtual machine (EVM), the Metamask wallet, and smart contracts (SCs). This article introduces solarcoins, a digital currency for trading solar energy, which reduces human intervention while fostering trust, transparency, and privacy among EV users. The proposed solution ensures secure communication between CS operators and EV users, enhancing both security and traceability. The proposed solution ensures secure communication between CS operators and EV users, enhancing both security and traceability. To quantify the sustainability and efficiency of the proposed system, the framework performances are tested and evaluated by varying numbers and types (Read, Write, and Transfer) of transactions using Hyperledger caliper and Go Ethereum. The overhaul Performance metrics were measured under varied transaction rates and control parameters by varying the number of validator nodes (1 node to 5 nodes), such as transaction latency, throughput, resource utilization, and so on. The performance of three major functionsâopen, query, and transferâwas recorded and analyzed. The results show that the query transaction is faster than open and transfer and the latency increases linearly with increased transaction rate. At 1000 transaction per second, the open function has a latency of 260.22 s, whereas the query function has a latency of 104.12 s and the transfer function has a latency of 345.73 s. The average memory usage for 1node-clique is 1224.0 MB, while it is 76.8 MB for 5node-clique. Results reveal that with an increase in the number of cliques (Validator CSs), memory utilization decreased linearly. This happens because all framework transactions are distributed across each EV CS network. The SCs deployment and operational costs were measured. Complexity analysis reveals that functions, such as getStation, getUser, getStationState, etc., exhibit constant time complexity O(1), while the registerUser and addStation functions have linear space and time complexity O(n).
With 1.92 million tons of carbon dioxide equivalent traded, the value of carbon credits under the T-VER project was estimated to be 146.7 million baht as of mid-2022. But compared to Thailand's total greenhouse gas emissions, which were 257.77 million tons of carbon dioxide equivalent in 2021, this trading volume is minuscule. Given this importance, the researchers see challenges in developing a mechanism for creating carbon credit assets in the form of NFTs and a support system to drive the carbon credit trading process. This article aims to apply a Non-Fungible Token (NFT) to enhance a credit carbon system. Existing systems often face challenges related to transparency, accountability, and traceability. This explores the potential integration of NFT into carbon credit systems to enhance transparency and traceability. A concept to address these challenges and optimize the functioning of carbon credit systems in Thailand. Including the theoretical framework, technical aspects, potential benefits, and challenges of integrating NFTs, a Blockchain base that is part of the cyber security framework for data protection in the digital world, into carbon credit systems. The researchers see challenges in developing a mechanism for creating carbon credit assets in the form of NFTs and a support system to drive the carbon credit trading process, with a primary focus on Cyber security standards.
The âgas feeâ paid for inclusion in the blockchain is analyzed in two parts. First, we consider how âeffortâ in terms of resources required to process and store a transaction turns into a âgas limit,â which, through a fee comprised of the âbaseâ and âpriority feeâ in the current version of Ethereum, is converted into the cost paid by the user. We adhere closely to the Ethereum protocol to simplify the analysis and to constrain the design choices when considering âmultidimensional gas.â Second, we assume that the âgasâ price is given deus ex machina by a fractional OrnsteinâUhlenbeck process and evaluate various derivatives. These contracts can, for example, mitigate gas cost volatility. The ability to price and trade âforwardsâ in addition to the existing âspotâ inclusion into the blockchain could enable users to hedge against future cost fluctuations. Overall, this article offers a comprehensive analysis of gas fee dynamics on the Ethereum blockchain, integrating supply-side constraints with demand-side modelling to enhance the predictability and stability of transaction costs.
H. Miri, Rajaa Naji El Idrissi, Mehdi Najib, A. NAIT SIDI MOH · 5 authors
The electrification of the transportation sector, via the integration of battery electric-powered vehicles (BEV), is one of the solutions, which could help in reducing greenhouse gas (GHG) emission. Smart charging techniques with bidirectional flow, in which the electric power can flow back and forth (i.e., V2G and G2V) from/into the grid according the peak hours have been recently proposed for improving power quality and regulating frequency/voltage of the utility grid. In this paper, we aim to develop a blockchain-based IoT platform for peer-to-peer energy trading between BEV and smart buildings management systems in the context of home healthcare by using Hyperledger Besu; a private network based on Ethereum with the use of its consensus algorithm Clique. The developed platform's prototype made a success transactions of energy trading which makes renewable energy available to everyone. Moreover, the concrete implementation of consensus, transaction record layout, and self-implemented smart contracts make Hyperledger Besu a green framework for implementing the proposed blockchain-IoT system.
Md. Ramjan Ali, Sharfuddin Ahmed Khan, YaĆanur Kayıkçı, Muhammad Shujaat Mubarik
Purpose Blockchain technology is one of the major contributors to supply chain sustainability because of its inherent features. However, its adoption rate is relatively low due to reasons such as the diverse barriers impeding blockchain adoption. The purpose of this study is to identify blockchain adoption barriers in sustainable supply chain and uncovers their interrelationships. Design/methodology/approach A three-phase framework that combines machine learning (ML) classifiers, BORUTA feature selection algorithm, and Grey-DEMATEL method. From the literature review, 26 potential barriers were identified and evaluated through the performance of ML models with accuracy and f-score. Findings The findings reveal that feature selection algorithm detected 15 prominent barriers, and random forest (RF) classifier performed with the highest accuracy and f-score. Moreover, the performance of the RF increased by 2.38% accuracy and 2.19% f-score after removing irrelevant barriers, confirming the validity of feature selection algorithm. An RF classifier ranked the prominent barriers and according to ranking, financial constraints, immaturity, security, knowledge and expertise, and cultural differences resided at the top of the list. Furthermore, a Grey-DEMATEL method is employed to expose interrelationships between prominent barriers and to provide an overview of the cause-and-effect group. Practical implications The outcome of this study can help industry practitioners develop new strategies and plans for blockchain adoption in sustainable supply chains. Originality/value The research on the adoption of blockchain technology in sustainable supply chains is still evolving. This study contributes to the ongoing debate by exploring how practitioners and decision-makers adopt blockchain technology, developing strategies and plans in the process.
This paper has two equally important research objectives. The first aim of the research is to identify key research areas addressed in scientific publications that simultaneously relate to blockchain, energy, and sustainability. In turn, the identification of green research areas in these publications is the second research aim. The indicated research aims were achieved on the basis of a bibliometric review of 205 scientific publications from 2017-2023 (Scopus database). By means of a systematic literature review, 25 different key research areas were identified. In turn, the classic literature review identified 18 green research areas (e.g. green blockchain). At the same time, no green issue was identified as a key research area. The results can inspire researchers looking for research gaps around blockchain and sustainability issues. Among the recommendations for stakeholders, the need for further research around blockchain technology, the development of a regulatory framework, or educational issues were highlighted.
Al Mothana Al Shareef, Serap Ulusam Seçkiner, Bilal Eid, Hasan Abumeteir
Recently, artificial intelligence (AI) and blockchain have become two of the most trending and disruptive technologies. Blockchain technology can automate payment in cryptocurrency and provide access to a shared ledger of data, transactions, and logs in a decentralized, secure, and trusted manner. In addition, with smart contracts, blockchain has the ability to govern interactions among participants with no intermediary or a trusted third party. AI, on the other hand, offers intelligence and decision-making capabilities to machines similar to humans. This review presents a detailed survey on blockchain and AI basics and features. This paper provides a review of the literature and a brief on the integration of blockchain and AI applications in multiple areas. We also identify some sole cases of blockchainâAI integration in the energy sector with current use cases. Eventually, we discuss research advantages and challenges associated with integrating blockchain with AI in the energy domain.
The environmental impact of Bitcoin mining has raised severe concerns considering the expected growth of 30% by 2030. This study aimed to develop a Life Cycle Assessment model to determine the carbon dioxide equivalent emissions associated with Bitcoin mining, considering material requirements and energy demand. By applying the impact assessment method IPCC 2021 GWP (100 years), the GHG emissions associated with electricity consumption were estimated at 51.7 Mt CO2 eq/year in 2022 and calculated by modelling real national mixes referring to the geographical area where mining takes place, allowing for the determination of the environmental impacts in a site-specific way. The estimated impacts were then adjusted to future energy projections (2030 and 2050), by modelling electricity mixes coherently with the spatial distribution of mining activities, the related national targeted goals, the increasing demand for electricity for hashrate and the capability of the systems to recover the heat generated in the mining phase. Further projections for 2030, based on two extrapolated energy consumption models, were also determined. The outcomes reveal that, in relation to the considered scenarios and their associated assumptions, breakeven points where the increase in energy consumption associated with mining nullifies the increase in the renewable energy share within the energy mix exist. The amount of amine-based sorbents hypothetically needed to capture the total CO2 equivalent emitted directly and indirectly for Bitcoin mining reaches up to almost 12 Bt. Further developments of the present work would rely on more reliable data related to future energy projections and the geographical distribution of miners, as well as an extension of the environmental categories analyzed. The Life Cycle Assessment methodology represents a valid tool to support policies and decision makers.
Muhammad Athar, Bin Li, Zaid Bin Tariq Baig, Ali Muqtadir · 6 authors
The integration of blockchain technology in demand response (DR) systems offers a transformative approach to enhancing energy management within smart grids (SGs). This paper explores the benefits, technical challenges, regulatory and policy issues, and adoption barriers associated with blockchain-enabled DR systems. Blockchain technology provides a decentralized and secure platform for managing DR programs, facilitating Peer-to-Peer (P2P) energy trading, and ensuring transparent and tamper-proof energy transactions. Despite its potential, the integration of blockchain with DR systems faces significant technical challenges, including scalability, interoperability, and high energy consumption. Transitioning to energy-efficient consensus mechanisms such as Proof of Stake (PoS) and Proof of Energy Efficiency (PoEE) can address these issues. Regulatory complexities and the need for supportive policies also pose challenges, requiring engagement with regulatory bodies and the promotion of policies that incentivize energy efficiency and the use of renewable energy sources. Additionally, overcoming resistance from stakeholders and ensuring market readiness are critical for the adoption of blockchain-enabled DR systems. By addressing these challenges with targeted solutions, the integration of blockchain technology with DR systems can significantly enhance energy efficiency and sustainability. This paper provides a comprehensive overview of the current state of research, highlighting both the potential benefits and the challenges that need to be addressed to realize the full potential of this innovative approach to energy management.
Based on the provincial panel data from China, this study explores the impact of digital finance on provincial carbon productivity. Further, the regional heterogeneity and spatial spillover effect, the moderating effects of financial supervision and environmental decentralization, and the mediating effect of green technology innovation are analyzed. The results show that digital finance can significantly improve provincial carbon productivity, and clearly promote carbon productivity in the underdeveloped provinces (i.e., central and western regions), but not in the economically developed provinces (i.e., eastern region). Digital finance has a positive spatial spillover effect on carbon productivity. In addition, financial supervision and environmental decentralization play moderating effects in the impact of digital finance on carbon productivity. Green technology innovation plays a partial mediating effect in the impact of digital finance on carbon productivity. This study provides a reference for improving carbon productivity and developing a low-carbon economy.
The trinity of global warming, climate change, and air pollution casts an ominous shadow over society and the environment. At the heart of these threats lie carbon emissions, whose reduction has become paramount. Blockchain technology and the internet of things (IoT) emerge as innovative tools for establishing an efficient carbon credit exchange. This paper presents a blockchain and IoT-centric platform for carbon credit exchange, paving the way for transparent, secure, and effective trading. IoT devices play a pivotal role in monitoring and verifying carbon emissions, safeguarding the integrity and accountability of the trading process. Blockchain technology, with its decentralized and immutable nature, empowers the platform with transparency, reduced fraud, and enhanced accountability. This platform aims to arm organizations and individuals with the ability to actively curb carbon emissions, fostering collective efforts towards global pollution reduction goals.