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The Chinese electric power industry, including its coal industry and other energy industries that are not efficient, contributes to China’s serious energy shortages and environmental contamination. The governing authority considers energy conservation to be one of the most prominent national targets, and has formulated various plans for decarbonizing the power system. Applying the trans-log cost function, this paper examined the trans-log cost function to analyze the potential inter-factor substitution among energy, capital and labor. We also investigated what role human capital played in energy substitution for the electric power sector during the period from 1981 to 2017. Three key results were derived: (1) energy is price-insensitive, (2) there exists large substitution sustainability between both capital and labor with energy, and (3) human capital input not only enhances the extent of energy substitutability with capital and labor but also is a substitute to energy itself. These findings imply that the liberalization of the electric price mechanism is conducive to lessening energy use and augmenting non-energy intensiveness, and that energy conservation technology could become more sustainable by investing more capital in the electricity sector, thereby achieving a capital–energy substitution and a decrease of CO2 emissions. We further suggest that the priority for the Chinese electric power industry should be to attach more importance to increasing human capital input.

Abstract Compared with other traditional energy sources, renewable energy, which results the less pollution and has numerous resources, is a significant factor in addressing the current issues of the serious environmental pollution and the resource depletion. Large-scale renewable energy integrated to the grid could bring change in both morphological structure and operation modes of energy transmission. Therefore, it is necessary to research the evolution mechanism of the future transmission network with a high proportion of the renewable energy. In this paper, an evolution framework of power system with high proportion of renewable energy is proposed. Firstly, a network equivalence and simplification based on power transfer distribution factors (PTDFs) is proposed, which can effectively simplify the decision-making process of evolution of large-scale power system. Then, an annual production simulation (8760 h) which takes into account renewable energy and load fluctuations is used to find out the bottleneck of the power grid. Based on the above methods, evolution strategy of power system with high proportion of renewable energy is studied for finding out optimal expansion strategy. A real power system of Zhejiang province is used as a test system. Test results demonstrate the feasibility of the proposed evolution framework.

Abstract Bio-based polyurethane (BPU) foams were successfully prepared using hydrothermally liquefied wheat straw (WS) to substitute a mass fraction of up to 50% of polyols. Response surface methodology (RSM) based on central composite design (CCD) was employed to optimize four process parameters: NCO/OH molar ratio, loading of crosslinking agent (glycerol), loading of catalyst (a mixture of triethylene diamine, stannous octoate, and triethanolamine), and loading of blowing agent (water) for the maximum compression strength of the rigid BPU foams. With the quadratic orthogonal regression model, verified by experimentation, the maximum compression strength of approximately 180 kPa was obtained at the following optimal conditions: NCO/OH molar ratio of 1.24:1, glycerol addition of 12.11%, catalyst loading of 0.76%, and blowing agent addition of 1.31% in relation to the total mass of polyols. The BPU foam prepared at the optimal conditions exhibits good thermal conductivity (0.045 Wm−1K−1) and thermal stability, comparable to those of a reference foam prepared with 100% PPG400.

SignificanceEstimates of nutrient allocation in different plant tissues and the relationships between the nutrient contents and photosynthetic capacity are critical to predicting ecosystem carbon sequestration under global change. Here, we provide an assessment of large-scale patterns of community-level nitrogen and phosphorus concentrations in different plant tissues and then examine how nutrient allocations are coupled with plant productivity. The results show that nutrient concentrations in leaves are less responsive to abiotic environments than those in woody stems and roots (stable leaf nutrient concentration hypothesis); the relationships between vegetation primary productivity and leaf nutrient contents are stronger when less nutrients are allocated to the woody tissues (productivity–nutrient allocation hypothesis) and are stronger in deciduous than in evergreen vegetation (productivity–leaf lifespan hypothesis).

A promising technology for renewable energy is energy piles used to heat and cool buildings. In this research, the effects of bio-cementation via microbially induced calcite precipitation (MICP) using mixed calcium and magnesium sources and the addition of fibres on the thermal conductivity of soil were investigated. Firstly, silica sand specimens were treated with cementation solutions containing different ratios of calcium chloride and magnesium chloride to achieve maximum thermal conductivity improvement. Three treatment cycles were provided, and the corresponding thermal conductivity was measured after each cycle. It was found that using 100% calcium chloride resulted in the highest thermal conductivity. This cementation solution was then used to treat bio-cemented soil samples containing fibres, including polyethylene, steel and glass fibres. The fibre contents used included 0.5%, 1.0% and 1.5% of the dry sand mass. The results show that the glass fibre samples yielded the highest thermal conductivity after three treatment cycles, and SEM imaging was used to support the findings. This research suggests that using MICP as a soil improvement technique can also improve the thermal conductivity of soil surrounding energy piles, which has high potential to effectively improve the efficiency of energy piles.

Cold-start (subzero startup) capability of polymer electrolyte fuel cell (PEFC) is of great importance. In this paper, the effects of the micro-porous-layer (MPL), varying start-up temperatures, start-up current density variation on the cold-start operation are investigated. We found PEFC with anode micro-porous-layer (AMPL), compared with one with CMPL, has higher possibility of successful cold start. By analyzing the anode and cathode pressure revolution of PEFC, the effect of MPL on the super cooled water removal and ice formation at different temperatures (-7,-10,-15 and-20℃) are discussed . In addition, we investigate the ice distribution in MEA through the X-ray device, by comparing the initial image when fuel cells shut down (before the produce the water) and final image after failed cold-start. We also explore the negative voltage phenomenon in the initial process of cold-start operation.

Chromium (Cr) exposure during gestation causes malformations in animal experiments. In this multicenter case-control study, we initially involved 130 orofacial clefts (OFCs) and 260 controls to assess the association between Cr concentration and risk for OFCs. Then, umbilical cord serum (49 vs. 119) and cord tissue (84 vs. 142) were used to validate the association between Cr and OFCs. We found that maternal serum Cr concentrations in OFC cases were significantly higher than those in controls. Compared with the lowest tertile of maternal serum Cr concentration, the highest tertile of Cr increased the risk for OFCs [OR = 2.14 (1.14-4.05)]. In the validation cohort of umbilical cord serum and tissue, higher concentrations of Cr were associated with increased risks for OFCs in a dose-dependent manner (all Ps for trends <0.05). Cr concentrations in maternal serum and cord serum showed a positive correlation. The Cr concentration in cord serum was inversely correlated with egg and milk consumption frequencies, and the Cr concentration in cord tissue was positively associated with indoor coal burning. In conclusion, prenatal Cr exposure is a risk factor for OFCs, and indoor coal burning during pregnancy may be one of the sources of Cr exposure.

Pedestrian inertial navigation technology plays an important role in indoor positioning technology. However, low-cost inertial sensors in smart devices are affected by bias and noise, resulting in rapidly increasing and accumulating errors when integrating double acceleration to obtain displacement. The data-driven class of pedestrian inertial navigation algorithms can reduce sensor bias and noise in IMU data by learning motion-related features through deep neural networks. Inspired by the RoNIN algorithm, this paper proposes a data-driven class algorithm, RBCN-Net. Firstly, the algorithm adds NAM and CBAM attention modules to the residual network ResNet18 to enhance the learning ability of the network for channel and spatial features. Adding the BiLSTM module can enhance the network’s ability to learn over long distances. Secondly, we construct a dataset VOIMU containing IMU data and ground truth trajectories based on visual inertial odometry (total distance of 18.53 km and total time of 5.65 h). Finally, the present algorithm is compared with CNN, LSTM, ResNet18 and ResNet50 networks in VOIMU dataset for experiments. The experimental results show that the RMSE values of RBCN-Net are reduced by 6.906, 2.726, 1.495 and 0.677, respectively, compared with the above networks, proving that the algorithm effectively improves the accuracy of pedestrian navigation.

Abstract To alleviate the shortage of natural gas resource and ease carbon emissions, a novel solar-driven combined cooling, heating and power (CCHP) system is designed and optimized using the genetic algorithm in the work. Different from the process of direct combustion in a conventional CCHP system, natural gas is firstly converted into syngas by a solar-driven natural gas reforming step, which is consumed in an efficient tri-generation system. Energy, economic and environmental evaluations on five office buildings in different climate zones in China are implemented to validate the advantages of the proposed system. Results show that the annual maximum primary energy saving, total cost saving, and CO2 emission reduction are 69.76%, 49.80%, and 71.55%, respectively. The system located in severe cold zones, where solar energy is abundant and building requires more heat load in whole year, achieves the highest benefits in comparison with separate systems. Furthermore, the sensitivities on the price fluctuations of electricity, natural gas and solar field to the system profits are investigated, which indicates that the influence of electricity price on the system performance is the most significant. Thus, a promising method for reducing the natural gas consumption and improving the utilization efficiency of solar energy is provided.