Cryptocurrencies and their Energy Consumption

Urban water resources management with energy constraint and carbon emission intensity under uncertainty: A dual objective optimization model

This, together with the related term Bitcoin, was a revolution in blockchain as envisioned by the mystery character Satoshi Nakamoto up to 2008. All this changes the very way the foundations of digital exchange and storage were thought about: decentralized, transparent, immutable, the very fundamentals of Distributed Ledger Technology enabling safe data exchange without an intermediary. The blockchain is fundamentally a chain of blocks carrying information about transactions, including times and cryptographic hashes, each of these connecting to the previous one in one unbroken chain, for which no modification is viable. The whole design of Blockchain has been to solve a number of issues, including double spending, fraud, and inefficient records, with distributed nodes and consensus mechanisms such as Proof of Work and Proof of Stake, facilitated by cryptographic keys. Other areas beyond cryptocurrency where quite a number of innovative uses are cut across include supply chain, healthcare, financial, and real estate sectors. For example, while the supply chain process is being promoted to become effective and transparent in order to ensure the origin and quality of the product, adding to the guarantee that the user's personal health information will not be accessed and tampered with, blockchain uses smart contracts in automating agreement processes within the contract. All of them are expecting cost reduction, operating efficiencies enhancement, enhanced securities of many industries. Anyhow, there exist quite a number of serious obstacles standing in the way of the wide application of blockchain technology. Firstly, the problem of scalability has still been an issue whereby the network performance tends to be problematic when users are increased. Besides, energy wasting cannot be ignored-apparently mostly a challenge from the PoW kind of system proved to be consuming too much energy, standing big on the road to sustainability. Of course, the mere lack of any kind of international rules and standards is already a complication in making them work. It also underlines failures in the adoption of the system or in decentralizing and is still an open technical and organizational challenge on how to combine blockchain with traditional structures. Their solutions require compounding ideas: sharding of blockchain to make it big, off-chain solutions for the blockchain to be many but thin, and provision of amicable solution consensus mechanisms for environmental conservation. Besides coherent policy vision, in addition to the existing cornerstones of regulation besides well-laid-out standards of interoperability, it is important to create confidence and give a road map across different industries. This paper hereby conceptually reviews the literature with respect to how the blockchain technology was designed to show revolutionary capability in the different fields and what keeps on tormenting it with its future.KEYS: Blockchain technology; Distributed Ledger; Decentralization; Cryptographic keys; Consensus mechanisms; Proof of Work; Proof of Stake; Smart contracts; Supply chain management; Data immutability; Transparency; Scalability; Energy consumption; Challenges to regulatory bodies; Security vulnerability; Sharding; off- chain processing; Interoperability; Applications using blockchain; Architecture of blockchain.

The implications of China’s investment-driven economy on its energy consumption and carbon emissions

Traditional blockchain consensus mechanisms, such as Proof of Work (PoW) and Proof of Stake (PoS), face significant challenges related to the centralisation of validators and miners, environmental impact, and trustworthiness. While PoW is highly secure, it is energy-intensive, and PoS tends to favour wealthy stakeholders, leading to validator centralisation. Existing mechanisms lack fairness, and the aspect of sustainability is not considered. Moreover, it fails to address social trust dynamics within validator selection. To bridge this research gap, this paper proposes Proof of Friendship (PoF)—a novel consensus mechanism that leverages social trust by improving decentralisation, enhancing fairness and sustainability among the validators. Unlike traditional methods that rely solely on computational power or financial stakes, PoF integrates friendship-based trust scores with geo-location diversity, transaction reliability, and sustainable energy adoption. By incorporating a trust graph, where validators are selected based on their verified relationships within the network, PoF mitigates the risks of Sybil attacks, promotes community-driven decentralisation, and enhances the resilience of the blockchain against adversarial manipulation. This research introduces the formal model of PoF, evaluates its security, decentralisation, and sustainability trade-offs, and demonstrates its effectiveness compared to existing consensus mechanisms. Our investigation and results indicate that PoF achieves higher decentralisation, improved trustworthiness, reduced validator monopolisation, and enhanced sustainability while maintaining strong network security. This study opens new avenues for socially aware blockchain governance, making consensus mechanisms more equitable, efficient, and environmentally responsible. This consensus mechanism demonstrates a holistic approach to modern blockchain design, addressing key challenges in trust, performance, and sustainability. The mechanism is tested theoretically and experimentally to validate its robustness and functionality. Processing latency (PL), network latency (NL) [transaction size/network speed], synchronisation delays (SDs), and cumulative delay per transaction are 85 ms, 172 ms, 1802 ms, [PL + NL + SD] 2059 ms, respectively.

As approaching the era of Ethereum 2.0, the already unique and innovative cryptocurrency will witness a game-changing upgrade, and in this context, there is a lively discussion of the Proof of Work (PoW) and Proof of Stake (PoS) consensus mechanism. Moving from a PoW consensus mechanism to a PoS consensus mechanism is one of the most anticipated changes in this update. A close comparison of the two most popular consensus mechanisms, PoW and PoS, provides some strengths and drawbacks to these mechanisms. This comparison then becomes the building block to identifying the reasons behind Ethereum's upgrade to Proof of Stake. With the help of the comparison, this paper identifies a few drawbacks of the PoW consensus mechanism that Ethereum is currently facing. This paper finds that Ethereum's shift to PoS has indeed reduced the drawbacks of the Proof of Work consensus mechanism, mainly in terms of energy consumption, transaction cost, and confirmation speed.

Facing the challenge of climate change, forecasts of energy demand and carbon emissions demand are a key requirement for India to ensure energy security and the balance economic growth. The authors calculate the optimal economic growth under the balance economic growth path from 2009 to 2050 in India based on the economy-carbon dynamic model. Combination of Intergovernmental Panel on Climate Change (IPCC) 2006 edition of the formula of carbon emissions, energy intensity model, and population model, it gets the carbon emissions demand caused by energy consumption for time span 1980-2008. Then, it estimates the energy consumption demand and carbon emissions demand under the balance economic growth path from 2009 to 2050. The results show that the cumulative amount of energy demand and carbon emissions demand in India for the time span 2009 to 2050, are 44.65 Gtoe and 36.16 Gt C, separately. The annual demand of energy consumption and carbon emissions for India show an inverted U curve from 2009 to 2050. The demand of energy consumption and carbon emissions will peak in 2045, and the peak values are 1290.74 Mtoe and 1045.98 Mt C. Furthermore, India's per capita energy consumption demand and carbon emissions demand also appear maximum values, which are separately 0.81 toe and 0.65 t C.

This work aims to analyze the impact of population aging on the relationship between economic growth and carbon emissions, and the relationship between energy consumption and carbon emissions. To this end, based on the panel data of 36 OECD countries from 1996 to 2016, the panel threshold regression model was developed. In the model, per capita carbon emissions are the explained variables, economic development (per capita GDP) and per capita energy consumption are the core explanatory variables of the two models respectively, population aging is the threshold variable, population size, technological innovation level, the degree of urbanization, industrial structure and energy intensity are control variables. The empirical results show that there is a population aging threshold effect between per capita GDP and per capita carbon emissions, and between per capita energy consumption and per capita carbon emissions. This means that population aging is an important factor that affects the relationship between economic growth and carbon emissions, as well as energy consumption and carbon emissions. Although economic growth and carbon emissions, energy consumption and carbon emissions were coupled, the coupling state decline when the population aging crosses the threshold value. This indicates that the population aging contributes to the decoupling of the economic growth and carbon emissions, and the decoupling of energy consumption and carbon emissions. Finally, on the basis of the proposed model, a robust analysis of the variable of trade openness was conducted to prove the validity of this research.

To assess whether China’s emissions will peak around 2030, we forecast energy consumption and carbon emissions in China. We use an agent-based model driven by enterprises’ innovation. Results show some differences in both energy consumption peaks and carbon emission peaks when we compare trends at different levels. We find that carbon emissions and energy consumption will peak in 2027 and 2028, respectively. However, the primary, secondary, and tertiary industries will reach energy consumption in different years: 2023, 2029, and 2022, respectively, and reach carbon emission peaks in 2022, 2028, and 2022, respectively. At the sectoral level, we find a wider range of energy consumption peaks and carbon emission peaks. Peak energy consumption occurs between 2020 and 2034, and peak carbon emissions between 2020 and 2032. Commercial and catering businesses, utilities and resident services, and finance and insurance achieve peak energy consumption and carbon emissions earliest in 2020, while building materials and other non-metallic mineral products manufacturing and metal products manufacturing are the two latest sectors to reach peak energy consumption and emissions, in 2034 and 2032, respectively.

Against the backdrop of the increasing scarcity of natural mineral aggregates and the underutilization of excessive steel slag resources, extensive research has confirmed the applicability of steel slag as a road aggregate and its favorable pavement performance properties. However, systematic quantitative assessments of steel slag asphalt pavement (SSAP) across multiple dimensions, including environmental and economic benefits, remain relatively limited. Among SSAP with 100% replacement of coarse aggregates by steel slag, the material production stage exhibits the lowest energy consumption and carbon emissions; this is followed by SSAP with a 60% steel slag replacement ratio, while conventional asphalt pavement (CAP) with 0% replacement demonstrates the highest values. When the transportation distance for natural aggregates is 180 km and for steel slag is 60 km, SSAP with 100% steel slag replacement shows the minimal energy consumption and carbon emissions during the transportation stage, whereas CAP with 0% replacement records the highest. Notably, this relationship reverses in the construction stage. The total carbon emissions generated during the construction period for SSAP with steel slag replacement ratios of 0%, 60%, and 100% are 142,841.16 kg, 122,775.15 kg, and 119,220.11 kg, respectively. Specifically, CAP (0% replacement) exhibits the maximum total energy consumption and carbon emissions during construction, while SSAP with 100% steel slag replacement presents the minimum values. These results demonstrate that replacing natural aggregates with steel slag can effectively reduce energy consumption and carbon emissions during the construction of asphalt pavements.

How do energy consumption and environmental regulation affect carbon emissions in China? New evidence from a dynamic threshold panel model

Reducing energy consumption and carbon emissions of magnesia refractory products: A life-cycle perspective

Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives

This article focuses on the production stage of industrialized building components. Through the analysis of the measured data, it is concluded that the unilateral carbon emissions generated by the consumption of natural gas in the steam curing stage of the northern factory account for more than 80% of the production process. The difference in natural gas consumption is the energy consumption and carbon emissions in the component production stage. The energy consumption and carbon emissions of the Nanfang (Longxin) plant in summer are higher than the transition season and winter; the power consumption and carbon emissions of auxiliary equipment in summer are close to 20% of the total carbon emissions during the production process, which is the season for energy consumption and carbon emissions in the component production stage The main reason for sexual differences.

The rapid development of High-Performance Computing (HPC) has driven technological advancements but also brought environmental challenges such as high energy consumption, carbon emissions, and electronic waste. This paper develops three core models to systematically analyze these issues and proposes sustainable solutions. Firstly, the paper analyzes the total energy consumption of global HPC centers, dividing it into computing-related energy and non-computing energy (e.g., cooling systems). In 2024, the estimated total energy consumption of the HPC industry was 205 terawatt-hours, which could reach 287 to 328 terawatt-hours under full load conditions. Secondly, by calculating the carbon emissions per kilowatt-hour of electricity, the paper estimates the global carbon emissions of the HPC industry in 2024 to be 7.24 million tons. The third model assesses the environmental impact of electronic waste generated by HPC systems, projecting that by 2030, HPC-related electronic waste will produce 112.8 million tons of carbon emissions, with disposal costs reaching 715 million USD and landfill costs of 6 million USD. Additionally, the study predicts the trends of energy consumption, carbon emissions, and electronic waste in the HPC industry by 2030. The research indicates that by adopting energy-saving technologies, accelerating the transition to renewable energy, and optimizing electronic waste management, the HPC industry can mitigate environmental hazards while leveraging its innovative potential and, based on this, proposes technical design recommendations such as energy-efficient hardware and software, reducing electronic waste, adopting cloud storage, and considering environmental impacts in technical design.

Consensus plays a crucial role in blockchain technology, with the delegated proof of stake (DPoS) consensus mechanism commonly utilized in both public and hybrid chains. However, the current DPoS mechanism faces challenges such as low node engagement in voting and potential security risks posed by malicious nodes. In response, we propose the DL-DPoS (deep link–delegated proof of stake) mechanism, which builds upon the DPoS framework. The DL-DPoS incorporates the LINK incentive mechanism to encourage inactive nodes to participate in voting and leader selection. Furthermore, a comprehensive credit scoring system based on wealth, performance, and stability is introduced to enhance the security of elected nodes. The verification process is optimized to involve all nodes except the leader node, and mechanisms are in place to handle malicious attacks by degrading or removing offending nodes and redistributing their responsibilities to the LINK group. Performance testing of the DL-DPoS mechanism, conducted through blockchain simulation tests using the GO language, shows a 23% increase in throughput compared to DPoS, with over 95% node participation and improved distribution of rights and equity. These results indicate the enhanced performance, security, and stability of the DL-DPoS consensus mechanism.