• Energy Research
• 2021-2025close
• 7. Clean energy close
• 12. Responsible consumption close
• Chinese Academy of Sciences close

Bioenergy is considered a sustainable substitute to fossil-fuel resources and the development of a prudent combination of renewable and innovative conversion technologies are essential for the valorization and effective conversion of biowaste to value-added commodities. Here, a negative pressure-induced carbonization process was proposed for the valorization of lignin-enriched biowaste precursor to bio-oil and environmental materials (biochar) at various temperatures. The high heating values (HHV) of the as-prepared biochars from the lignin enriched precursor under negative pressure (low-medium vacuum) were within 25.9-31.5 MJ/kg, which matched satisfactorily to the commercial charcoal. Whereas, the bio-oils produced from the lignin enriched precursor under vacuum conditions was a blend of complex aromatic and straight-chain hydro-carbons, including aldehyde, ketone, phenol, and furans, exhibiting ability as potential heating-oil with HHV within 21.2-28.2 MJ/kg. Moreover, the biochars produced under vacuum environments at higher temperature showed greater stability (22.5-35.9%) than those produced under N2 atmosphere.

The transition towards renewable energy is leading to an important strain on the energy grids. The question of designing and deploying renewable energy technologies in symbiosis with existing grids and infrastructure is arising. While current energy system models mainly focus on the energy transformation system or only investigate the effect on one energy vector grid, we present a methodology to characterize different energy vector grids and storage, integrated into the multi-energy and multi-sector modeling framework EnergyScope. The characterization of energy grids is achieved through a traditional energy technology and grid modeling approach, integrating economic and technical parameters. The methodology has been applied to the case study of a country with a high existing transmission infrastructure density, e.g., Switzerland, switching from a fossil fuel-based system to a high share of renewable energy deployment. The results show that the economic optimum with high shares of renewable energy requires the electric distribution grid reinforcement with 2.439 GW (+61%) Low Voltage (LV) and 4.626 GW (+82%) Medium Voltage (MV), with no reinforcement required at transmission level [High Voltage (HV) and Extra High Voltage (EHV)]. The reinforcement is due to high shares of LV-Photovoltaic (PV) (15.4 GW) and MV-wind (20 GW) deployment. Without reinforcement, additional biomass is required for methane production, which is stored in 4.8–5.95 TWh methane storage tanks to compensate for seasonal intermittency using the existing gas infrastructure. In contrast, hydro storage capacity is used at a maximum of 8.9 TWh. Furthermore, the choice of less efficient technologies to avoid reinforcement results in a 8.5%–9.3% cost penalty compared to the cost of the reinforced system. This study considers a geographically averaged and aggregated model, assuming all production and consumption are made in one single spot, not considering the role of future decentralization of the energy system, leading to a possible overestimation of grid reinforcement needs.

Triplet-triplet annihilation (TTA) upconversion has shown promising potentials in the augmentation of solar energy conversion. However, challenging issues exist in improving TTA upconversion efficiencies in solid-states, one of which is the back energy transfer from upconverted singlet annihilators to sensitizers resulting in decreasing upconversion emission. Here we present a light-harvesting molecular wire consisting of dendrons with 9,10-diphenylanthracene derivatives (DPAEH) at the periphery and para-phenylene ethynylene oligomers (PPE) as the wire core. The peripheral DPAEH antenna funnels singlet excitonic energy to the wire on a 12 ps timescale. Incorporating the molecular wire into the TTA upconversion solid consisting of the DPAEH annihilator and the porphyrin sensitizer evidently improves the upconversion quantum yield from 1.5% to 2.7% upon 532 nm excitation by suppressing the back energy transfer from the singlet annihilator to the sensitizer. This finding offers a potential route to use singlet energy light-harvesting architecture for enhancing TTA upconversion. Triplet-triplet annihilation (TTA) upconversion has shown promising potentials in the augmentation of solar energy conversion. However, challenging issues exist in improving TTA upconversion efficiencies in solid-states, one of which is the back energy transfer from upconverted singlet annihilators to sensitizers resulting in decreasing upconversion emission. Here we present a light-harvesting molecular wire consisting of dendrons with 9,10-diphenylanthracene derivatives (DPAEH) at the periphery and para-phenylene ethynylene oligomers (PPE) as the wire core. The peripheral DPAEH antenna funnels singlet excitonic energy to the wire on a 12 ps timescale. Incorporating the molecular wire into the TTA upconversion solid consisting of the DPAEH annihilator and the porphyrin sensitizer evidently improves the upconversion quantum yield from 1.5% to 2.7% upon 532 nm excitation by suppressing the back energy transfer from the singlet annihilator to the sensitizer. This finding offers a potential route to use singlet energy light-harvesting architecture for enhancing TTA upconversion.

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

It is critical and challenging to develop high performance transition metal phosphides (TMPs) electrocatalysts for oxygen evolution reaction (OER) to address fossil energy shortages. Herein, we report the synthesis of Co2P embedded in N-doped porous carbon (Co2P@N-C) via a facile one-step strategy. The obtained catalyst exhibits a lower overpotential of 352 mV for OER at a current density of 10 mA cm−2 and a small Tafel slope of 84.6 mV dec−1, with long-time reliable stability. The excellent electrocatalytic performance of Co2P@N-C can be mainly owed to the synergistic effect between the Co2P and highly conductive N-C substrate, which not only affords rich exposed active sites but also promotes faster charge transfer, thus significantly promoting OER process. This work presents a promising and industrially applicable synthetic strategy for the rational design of high performance nonnoble metal electrocatalysts with enhanced OER performance.

In the development of a Risk Monitor probabilistic safety assessment (PSA) model from the basic PSA model of a nuclear power plant, the modeling of common-cause failure (CCF) is very important. At present, some approximate modeling methods are widely used, but there lacks criterion of modeling accuracy and error analysis. In this paper, aiming at ensuring the accuracy of risk assessment and minimizing the Risk Monitor PSA models size, we present three basic issues of CCF model resulted from the changes of a nuclear power plant configuration, put forward corresponding modeling methods, and derive accuracy criteria of CCF modeling based on minimum cut sets and risk indicators according to the requirements of risk monitoring. Finally, a nuclear power plant Risk Monitor PSA model is taken as an example to demonstrate the effectiveness of the proposed modeling method and accuracy criteria, and the application scope of the idea of this paper is also discussed.

This paper proposes a series of parallel optimizations on a high-resolution ocean model, the LASG/IAP Climate System Ocean Model (LICOM), which was independently developed by the Institute of Atmospheric Physics of the Chinese Academy of Sciences. The version of LICOM that we used was LICOM 2.1. In order to improve the parallel performance of LICOM, a series of parallel optimization methods were applied. We optimized the parallelization scheme to tackle the problem of load imbalance. Some communication optimizations were implemented, including data packing, the application of the least communication algorithm, and the replacement of communications with calculations. Furthermore, for the calculation procedures, we implemented some mature optimizations and expanded functions in a loop. Additionally, a hybrid of MPI and OpenMP, as well as an asynchronous parallel IO, was used. In this work, the optimized version of LICOM 2.1 was able to achieve a speedup of more than two times compared with the original code. The parallelization scheme optimization and the communication optimization produced considerable improvement in performance in the large-scale parallelization. Meanwhile, the newly optimized LICOM could scale up to 245,760 processor cores. However, for the original version, there was no speedup when scaled up to over 10,000 processor cores. Additionally, the problem of jumpy wall time during the time integration process was also tackled with this optimization. Finally, we conducted a practical simulation from 1993 to 2007 by using the optimized version of LICOM 2.1. The results showed that the mesoscale vortex was well simulated by the model.

Abstract Cu2BaSn(S,Se)4 (CBTSSe) solar cells are emerging photovoltaic devices due to their high theoretical efficiencies of ~31%, environment-friendly and earth-abundant composition, low density of non-recombination defects, and so on. However, the record efficiency of CBTSSe solar cell is only 5.2%, showing the importance of studying their performance via numerical analysis to further enhance their practical efficiencies. In this paper, the effect of absorber and buffer layers on performances of Cu2BaSnS4 (CBTS) solar cells are firstly systematically studied via the SCAPS-1D software to provide a platform for the study of the effect of MoS2 interlayer on the performances of CBTS solar cells. The highest PCE of CBTS solar cell with a 30 nm CdS buffer layer is 11.87%. The PCE of CBTS solar cell with a 0.8 μm CBTS absorb layer is 12.51%, indicating that the CBTS solar cell is a potential low-cost solar cell due to its large optical absorption coefficient (α > 104 cm−1). The efficiency of CBTS solar cell is improved to 16.47% when the carrier concentration of CBTS is 1016 cm−3. The relationship between the performance of solar cell and the band gap, thickness, donor concentration, acceptor concentration of MoS2 interlayer is systematically investigated on the basis of the optimized efficiency. It is found that MoS2 interlayer plays an important role in the performance of CBTS solar cell. The p-type MoS2 has a beneficial effect on the efficiency improvement while the n-type MoS2 has a negative effect on the efficiency enhancement. The highest PCE of CBTS solar cell is as high as 18.28% when the thickness and the acceptor concentration of MoS2 are 4 nm and 1019 cm−3, respectively. Our simulation result provides a promising research direction to further improve the actual efficiency of the CBTS solar cell.

Wind power, as one of the primary clean energies, is an important way to achieve the goals of carbon peak and carbon neutrality. Therefore, high-resolution measurement and accurate forecasting of wind speed are very important in the organization and dispatching of the wind farm. In this study, several methodologies, including the mesoscale WRF (Weather Research and Forecasting(WRF) model, mathematical statistics algorithms, and machine learning algorithms, were adopted to systematically explore the predictability and optimization of wind speed of a Gobi grassland wind farm located in western Inner Mongolia. Results show that the rear-row turbines were significantly affected by upwind turbine wakes. The output power of upwind-group turbines was 591 KW with an average wind speed of 7.66 m/s, followed by 532 KW and 7.02 m/s in the middle group and 519 KW and 6.92 m/s in the downwind group. The higher the wind speed was, the more significantly the wake effect was presented. Intercomparison between observations and WRF simulations showed an average deviation of 3.73 m/s. Two postprocessing methods of bilinear interpolation and nearest replacement could effectively reduce the errors by 34.85% and 36.19%, respectively, with average deviations of 2.43 m/s and 2.38 m/s. A cycle correction algorithm named Average Variance–Trend (AVT) can further optimize the errors to 2.14 m/s and 2.13 m/s. In another aspect, the categorical boosting (CatBoost) artificial intelligence algorithm also showed a great performance in improving the accuracy of WRF outputs, and the four-day average deviation of 26–29 September decreased from 3.21 m/s to around 2.50 m/s. However, because of the influence of large-scale circulations, there still exist large errors in the results of various correction algorithms. It is therefore suggested through the investigation that data assimilation of the northwest and Mongolian plateau, boundary layer parameterization scheme optimization, and embedding of high-resolution topographic data could have great potential for obtaining more accurate forecasting products.