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The world's oceans, covering approximately 71 % of the Earth's surface, harbor vast wave energy resources, offering a potential solution to the pressing energy crisis and environmental pollution caused by fossil fuel combustion. In recent years, there has been a global surge in exploration and development of wave energy conversion technologies, aimed at effectively harnessing wave energy to realizing sustainable and intelligent sea solutions. This comprehensive review examines the advancements, challenges and future research directions of current mainstream wave energy conversion technologies. Firstly, the distribution of global wave resources and energy conversion process involved in wave energy extraction are analyzed. Subsequently, various wave energy conversion technologies are meticulously classified based on their power take-off systems, and the strengths and challenges of each category are comprehensively investigated. Especially, a universal standard consisting of 5 key indicators has been established to evaluate and compare the characteristics of various wave energy conversion technologies based on different transduction mechanisms, providing comprehensive and intuitive valid references for developers with different needs. The evaluation reveals that the wave energy converters based on hybrid systems demonstrate significant promise as conversion technologies. Moreover, the review presents a summary and analysis of the latest advancements in the application of artificial intelligence within wave energy conversion technologies. This emerging integration of artificial intelligence showcases promising development and potential for further enhancing wave energy conversion systems. Lastly, the review explores the application and future research directions of wave energy conversion technologies. Notably, the investigation highlights the potential of developing a multi-energy complementary power generation system that can concurrently harness multiple renewable energy sources coexisting at sea. This concept represents a promising avenue for future research and development.

Integrating of carbon capture, utilization, and storage with poverty alleviation strategies presents an innovative and sustainable development paradigm. Regional poverty, often exacerbated by challenging geographical conditions, can be transformed into opportunities for carbon storage development, promoting energy and economic rebalancing while avoiding poverty and resource traps. By introducing an evaluation index grounded in Sustainable Development Goals and technical requirements, we achieve a harmonious balance between potential and economic development. Techno-economic analysis in coal plant renovation and oil field projects demonstrates this project triggers a 7.70% growth in local gross domestic product per capita, and a decrease of 4.85% in local carbon dioxide emissions. Construction costs in impoverished regions can be over 20% lower than in more affluent areas for projects of the same scale because of cheaper labor and lower transportation and storage costs, highlighting the cost-effectiveness of pursuing poverty alleviation through carbon capture, utilization, and storage in China. This paper also emphasized the carbon storage demand in future's energy transition of China. The status of policy implementation underscored the significant potential of carbon capture, utilization, and storage in contributing to poverty alleviation in the world's largest carbon emitter and developing country, potentially serving as a critical testbed globally.

A novel design for the energy storage by adsorption-absorption for the partial CO2 capture of the energy supply buildings with fixed CO2 emission is proposed. The new design successfully utilizes the attainment of the low energy consumption and implements energy storage through adsorption part, overcoming the deficiencies of poor selectivity through absorption part. Numerical approaches have been developed for modeling the adsorption-absorption procedure, while attaining satisfactory agreement with experimental data. The adsorption process is modeled based on the finite volume method, and the absorption process is simulated based on the double-film theory and the rate-based model. The issue of operating parameters upon system assessments has received considerable critical attention by numerical implementations. The results show that the mass fraction of CO2 in the flue gas has been increased to 39.0%. The comprehensive enhancement effects are instrumental at a height of 20 m in the absorption tower. As the CO2 concentration of the flue gas increases from 5.0% to 20.0%, the absorbent flow, absorber diameter, and reboiler specific load decrease by 13.0%, 42.1%, and 16.6%, in respective. The present analysis and design will provide guidance and gain fresh prominence with advantages in the CO2 capture and purification. 

Energy consumption and permanent population are key indicators for evaluating resource equity and social development, with land use serving as their spatial carrier and the foundation for efficient governance. This study develops a Land-Energy-Population Nexus system to address the specific demands of the Sustainable Development Goals. It evaluates the sources of energy consumption and the spatiotemporal distribution of the population, elucidates the carrying capacity and mechanisms, and enables land use subdivision. A land-energy-population correlation model is established to identify the marginal impact curves and interaction effects of land use on energy consumption and population. A high-performance simulation model driven by a geographic grid reduction algorithm supports large-scale, multi-indicator prediction. China, the world's most populous country and largest energy consumer, is selected as the case study. Energy consumption and population are characterized at the third administrative level for 2025, with key indicators projected for 2030. Cities are clustered into three development types, and 259,743 simulation experiments are conducted to explore the role of land use optimization in promoting more equitable development. Key findings include: (1) Scale effects dominate the marginal impacts of land use. Controlling urban residential land within 22.78–96.65 km2 and other industrial land below 17.52 km2 helps manage energy intensity. (2) For industrial cities, an optimized structure with 9.6 % large-scale industrial land, 37.5 % other industrial land, and 24.9 % mixed-use land balances industrial growth and energy efficiency. (3) Decentralizing and intensifying large-scale industrial land contributes to overall energy control, but may pose risks of inequality due to core-area population siphoning and industrial-center energy growth. 

Rooftop photovoltaic (RPV) is often understood as a niche contribution to climate change mitigation. However, the global potential of RPVs to mitigate global warming is unknown. Here we map the global rooftop area at 1-km resolution, quantifying 286,393 km2 of rooftops worldwide through geospatial data mining and artificial intelligence techniques. Using nine advanced Earth system models from the coupled model intercomparison project phase 6, we reveal that RPVs could substantially contribute to reducing global temperatures by 0.05-0.13 degrees C before 2050. Region-specific analysis underscores the variability in RPV potential and the necessity of tailored approaches to optimize RPV deployment, considering local solar resources, existing infrastructure and grid carbon intensity. Our findings reveal that leveraging RPV systems offers a viable and impactful strategy for reducing carbon footprints and combating climate change globally, while advocating targeted interventions to enhance the benefits of RPVs, particularly in areas with high solar radiation or rapid urbanization.

Enhancing the energy efficiency of buildings significantly relies on monitoring indoor ambient temperature. The potential limitations of conventional temperature measurement techniques, together with the omnipresence of smartphones, have redirected researchers' attention towards the exploration of phone-based ambient temperature estimation methods. However, existing phone-based methods face challenges such as insufficient privacy protection, difficulty in adapting models to various phones, and hurdles in obtaining enough labeled training data. In this study, we propose a distributed phone-based ambient temperature estimation system which enables collaboration among multiple phones to accurately measure the ambient temperature in different areas of an indoor space. This system also provides an efficient, cost-effective approach with a few-shot meta-learning module and an automated label generation module. It shows that with just 5 new training data points, the temperature estimation model can adapt to a new phone and reach a good performance. Moreover, the system uses crowdsourcing to generate accurate labels for all newly collected training data, significantly reducing costs. Additionally, we highlight the potential of incorporating federated learning into our system to enhance privacy protection. We believe this study can advance the practical application of phone-based ambient temperature measurement, facilitating energy-saving efforts in buildings.

This paper proposed a portable balloon-integrated photovoltaic system (BIPVS) deployed at low altitude. The inflatable and deflatable design enhances the proposed system flexibility and mobility, enabling it have a wider range of application scenarios. Case studies were conducted based on cities' data of Vasteras, Vancouver, New York, Shanghai and Hong Kong to evaluate 10,000 BIPVS's annual power generation potential. Mid-to-high latitudes are not suitable for photovoltaic power generation in winter due to snow and ice coverage. Excluding the unsuitable winter months, simulation results show that the average monthly power generation of the BIPVSs amounts to 3.921 GWh, 4.238 GWh, 4.275 GWh, 3.337 GWh, and 3.379 GWh, respectively, during the effective working months within a year, which shows the superior performance of mid-to-high latitudes over their low latitudes. Over the life cycle, the BIPVSs exhibit a cumulative power generation capacity, amounting to 479.492 GWh, 592.18 GWh, 672.105 GWh, 641.155 GWh, and 708.334 GWh, respectively, and their total profits are 79.614 million USD, 37.007 million USD, 75.146 million USD, 12.946 million USD, 107.369 million USD, accompanied by the return on investment of 218.6 %, 101.6 %, 206.3 %, 35.5 %, 294.8 %, respectively. These findings illustrate the significant energy and economic advantages and potential of BIPVS.

Self-powered smart buoys are widely used in sustainable sea, such as marine environmental monitoring. The article designs a self-powered and self-sensing point-absorber wave energy converter based on the two-arm mechanism. The system consists of the wave energy capture module, the power take-off module, the generator module and the energy storage module. As the core component of the wave energy converter, the power take-off module is mainly composed of a two-arm mechanism, which can convert the oscillation heave motion into unidirectional rotary motion. To evaluate the power generation performance of the system, the kinematic and dynamic models of the wave energy converter with the flywheel are established, and the disengagement and engagement phenomena of the flywheel are analyzed. The effectiveness of the prototype in capturing wave energy is verified through dry experiments in lab and field tests. The dry experiment reveals that the maximum output power of the system is 5.67 W, and the maximum and average mechanical efficiency are 66.63 % and 48.35 %, respectively. Additionally, the field test demonstrates that the peak output power can reach 92 W. Meanwhile, the generated electrical signals can be processed by deep learning algorithms to accurately identify different wave states. This high performance confirms that the proposed wave energy converter can meet its own energy needs by capturing wave energy in the marine environment, while also achieving self-sensing for wave condition monitoring. The system has great potential for promoting the development of intelligent sustainable sea in the future. 

Prioritizing electric power system decarbonization is crucial for meeting global carbon neutrality targets. However, the role of energy technology cost reduction driven by innovation in advancing carbon neutrality in the electric power system has not been well studied. To fill this gap, an integrated investment planning and operation model is developed to simulate the carbon neutral pathway in the electric power system over a 30-year period from 2020 to 2050. The learning curves with different learning rates are incorporated into the model to represent different energy technology innovation scenarios. According to our results, the advanced innovation scenario is projected to achieve carbon neutrality in the electric power system five years earlier compared with the conservative innovation scenario, with a cost savings of 465 billion CNY. In addition, both inter-regional and intra-regional collaboration facilitate the achievement of carbon neutrality in the electric power system at a reduced cost. 

Vibration energy harvesting technology is characterized by wide distribution, is pollution-free and independent of weather and climate, and is suitable for powering low-power sensors to ensure efficient and safe operation in freight railroads. This paper proposed an electromagnetic vibration energy harvester based on a series coupling input mechanism for the self-powered sensors in freight railroads. The design utilizes only one rack for vibration energy input to minimize the moment acting on the vibration source during the working process. Two pinions meshed with the rack convert the up and down vibrations into a two-way rotation. The one-way bearings and another pair of gears convert the opposite rotations of two parallel shafts into one-way rotation of the generator shaft, generating electricity. Supercapacitors and rectifier voltage regulator modules are utilized to store electrical energy efficiently. A peak power of 10.219 W and maximum mechanical efficiency of 64.31% is obtained in the experiment equipped with a flywheel under the 8 mm-4 Hz sinusoidal vibration excitation. The experimental results showed that the flywheel can enable the proposed harvester to achieve better power generation performance when the amplitude and frequency are relatively high.