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Strategies to save energy in the context of the energy crisis: a review
New technologies, systems, societal organization and policies for energy saving are urgently needed in the context of accelerated climate change, the Ukraine conflict and the past coronavirus disease 2019 pandemic. For instance, concerns about market and policy responses that could lead to new lock-ins, such as investing in liquefied natural gas infrastructure and using all available fossil fuels to compensate for Russian gas supply cuts, may hinder decarbonization efforts. Here we review energy-saving solutions with a focus on the actual energy crisis, green alternatives to fossil fuel heating, energy saving in buildings and transportation, artificial intelligence for sustainable energy, and implications for the environment and society. Green alternatives include biomass boilers and stoves, hybrid heat pumps, geothermal heating, solar thermal systems, solar photovoltaics systems into electric boilers, compressed natural gas and hydrogen. We also detail case studies in Germany which is planning a 100% renewable energy switch by 2050 and developing the storage of compressed air in China, with emphasis on technical and economic aspects. The global energy consumption in 2020 was 30.01% for the industry, 26.18% for transport, and 22.08% for residential sectors. 10–40% of energy consumption can be reduced using renewable energy sources, passive design strategies, smart grid analytics, energy-efficient building systems, and intelligent energy monitoring. Electric vehicles offer the highest cost-per-kilometer reduction of 75% and the lowest energy loss of 33%, yet battery-related issues, cost, and weight are challenging. 5–30% of energy can be saved using automated and networked vehicles. Artificial intelligence shows a huge potential in energy saving by improving weather forecasting and machine maintenance and enabling connectivity across homes, workplaces, and transportation. For instance, 18.97–42.60% of energy consumption can be reduced in buildings through deep neural networking. In the electricity sector, artificial intelligence can automate power generation, distribution, and transmission operations, balance the grid without human intervention, enable lightning-speed trading and arbitrage decisions at scale, and eliminate the need for manual adjustments by end-users.
Journal Article
China as a global clean energy champion : lifting the veil
\"This book considers China's role as a rising champion of clean energy and document the policy decisions and actions which have underpinned this evolution. It considers the construction of the world's largest fleets of advanced coal-fired power stations, wind farms and solar photovoltaic arrays, examines sustained efforts to reduce national GDP intensities of energy and CO2 emissions, and assesses the rhetoric of government announcements on national policy and international commitments, including the Thirteenth Five-year Plan for Energy (2016-2020). The book notably considers the factors that have supported these achievements, including the availability of large amounts of capital, the role of state-owned companies with soft budgetary constraints, and many forms of indirect support from local governments. It also explores the obstacles to reaching the formal goals of reducing air pollution and CO2 emissions as well as the costs and unintended consequences of these policies, and identifies those parts of the energy supply chain where the governance of energy has been less effective in terms of energy efficiency and environmental protection.\"-- Provided by publisher.
Book
Clean energy investment and financial development as determinants of environment and sustainable economic growth: evidence from China
Environmental sustainability has become one of the most common phrases in discussions about climate change. This study examines the impact of clean energy investment and financial development on environmental sustainability and China’s economic growth, using manufacturing value-added and urbanization as moderator variables from 1970 to 2016. We used advanced econometric methodologies for empirical estimations, used structural break unit root tests, fully modified least square, dynamic least square, and robust least square multiple regressions for long-run estimates. Overall, the results determine that clean energy investment is negatively associated with CO
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emissions and ecological footprint while positively associated with China’s economic growth. Financial development, manufacturing value-added, and urbanization are positively associated with CO
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emissions, ecological footprint, and China’s economic growth. Moreover, clean energy investment improves environmental sustainability at the expense of economic growth. Financial development, manufacturing value-added, and urbanization encourage economic growth at the expense of environmental sustainability. We argued that the local governments play a critical role in lifting the outstanding barriers to cleaner energy investment, addressing disincentives, including pricing carbon dioxide emissions, reforming inefficient nonrenewable fossil fuel subsidies, and addressing regulatory and market rigidities that can undesirably affect the attractiveness of clean energy investment. Policymakers are suggested to encourage green finance strategy for the financial sector to broader sustainable development objectives. At the heart of green manufacturing, industrialization policies are needed to integrate diverse intentions, like inclusive growth, environmental protection, and productivity through a wider range of economic, social, and environmental policy frameworks suitable for decoupling growth from social and environmental unsustainability.
Journal Article
Single‐atom catalysis for carbon neutrality
Currently, more than 86% of global energy consumption is still mainly dependent on traditional fossil fuels, which causes resource scarcity and even emission of high amounts of carbon dioxide (CO2), resulting in a severe “Greenhouse effect.” Considering this situation, the concept of “carbon neutrality” has been put forward by 125 countries one after another. To achieve the goals of “carbon neutrality,” two main strategies to reduce CO2 emissions and develop sustainable clean energy can be adopted. Notably, these are crucial for the synthesis of advanced single‐atom catalysts (SACs) for energy‐related applications. In this review, we highlight unique SACs for conversion of CO2 into high‐efficiency carbon energy, for example, through photocatalytic, electrocatalytic, and thermal catalytic hydrogenation technologies, to convert CO2 into hydrocarbon fuels (CO, CH4, HCOOH, CH3OH, and multicarbon [C2+] products). In addition, we introduce advanced energy conversion technologies and devices to replace traditional polluting fossil fuels, such as photocatalytic and electrocatalytic water splitting to produce hydrogen energy and a high‐efficiency oxygen reduction reaction (ORR) for fuel cells. Impressively, several representative examples of SACs (including d‐, ds‐, p‐, and f‐blocks) for CO2 conversion, water splitting to H2, and ORR are discussed to describe synthesis methods, characterization, and corresponding catalytic activity. Finally, this review concludes with a description of the challenges and outlooks for future applications of SACs in contributing toward carbon neutrality.
Good progress has been achieved in research on single‐atom catalysts (SACs) with nearly 100% atom utilization in terms of energy conversion and utilization involved in the process of “carbon neutrality.” Herein, SACs, including d‐, ds‐, p‐, and f‐blocks, for CO2 conversion, water splitting, and oxygen reduction reaction in fuel cells through photocatalytic, electrocatalytic, and thermocatalytic processes, are discussed. This will provide an understanding of the rapid development and practical applications of SACs for “carbon neutrality.”
Journal Article
Multi-Criteria Assessment for City-Wide Rooftop Solar PV Deployment: A Case Study of Bandung, Indonesia
The world faces the threat of an energy crisis that is exacerbated by the dominance of fossil energy sources that negatively impact the sustainability of the earth’s ecosystem. Currently, efforts to increase the supply of renewable energy have become a global agenda, including using solar energy which is one of the rapidly developing clean energies. However, studies in solar photovoltaic (PV) modelling that integrates geospatial information of urban morphological building characters, solar radiation, and multiple meteorological parameters in low-cost scope have not been explored fully. Therefore, this research aims to model the urban rooftop solar PV development in the Global South using Bandung, Indonesia, as a case study. This research also has several specific purposes: developing a building height model as well as determining the energy potential of rooftop solar PV, the energy needs of each building, and the residential property index. This study is among the first to develop the national digital surface model (DSM) of buildings. In addition, the analysis of meteorological effects integrated with the hillshade parameter was used to obtain the solar PV potential value of the roof in more detail. The process of integrating building parameters in the form of rooftop solar PV development potential, energy requirements, and residential property index of a building was expected to increase the accuracy of determining priority buildings for rooftop solar PV deployment in Bandung. This study shows that the estimated results of effective solar PV in Bandung ranges from 351.833 to 493.813 W/m2, with a total of 1316 and 36,372 buildings in scenarios 1 and 2 being at a high level of priority for solar PV development. This study is expected to be a reference for the Indonesian government in planning the construction of large-scale rooftop solar PV in urban areas to encourage the rapid use of clean energy. Furthermore, this study has general potential for other jurisdictions for the governments focusing on clean energy using geospatial information in relation with buildings and their energy consumption.
Journal Article
The effect of differentiating costs of capital by country and technology on the European energy transition
Cost of capital is an important driver of investment decisions, including the large investments needed to execute the low-carbon energy transition. Most models, however, abstract from country or technology differences in cost of capital and use uniform assumptions. These might lead to biased results regarding the transition of certain countries towards renewables in the power mix and potentially to a sub-optimal use of public resources. In this paper, we differentiate the cost of capital per country and technology for European Union (EU) countries to more accurately reflect real-world market conditions. Using empirical data from the EU, we find significant differences in the cost of capital across countries and energy technologies. Implementing these differentiated costs of capital in an energy model, we show large implications for the technology mix, deployment, carbon emissions and electricity system costs. Cost-reducing effects stemming from financing experience are observed in all EU countries and their impact is larger in the presence of high carbon prices. In sum, we contribute to the development of energy system models with a method to differentiate the cost of capital for incumbent fossil fuel technologies as well as novel renewable technologies. The increasingly accurate projections of such models can help policymakers engineer a more effective and efficient energy transition.
Journal Article