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Contained arsenic (As) and unsafe brackish groundwater irrigation can lead to serious As pollution and increase the ecological risk in cultivated soils. However, little is known about how Fe oxides and microbes affect As migration during soil irrigation processes involving arsenic-contaminated brackish groundwater. In this study, the samples (porewater and soil) were collected through the dynamic soil column experiments to explore the As migration process and its effect factors during soil irrigation. The results showed that the As concentration in porewater samples from the topsoil was enriched compared to that in the subsoil, and the main solid As fractions were strongly adsorbed or bound to amorphous and crystalline Fe oxides. The aqueous As concentration and the solid As fractions indicated that reductive dissolution and desorption from amorphous Fe oxides were the primary mechanisms of As release at the topsoil and subsoil, respectively. Meanwhile, Sphingomonas_sp., Microvirga_ossetica and Acidobacteriota_bacterium were the dominant microbes affecting As biotransformation by arsenate reductase gene (arsC) expression. Accompanied by the Eh and competitive ions concentration change, amorphous Fe oxide dissolution increased to facilitate the As release, and the changes in the microbial community structure related to As reduction may have enhanced As mobilization in soils irrigated by As-containing brackish groundwater. [ABSTRACT FROM AUTHOR]

Precise wind power forecasting is essential for the successful integration of wind power into the power grid and for mitigating the potential effects of wind power on the power system. To enhance the precision of predictions, a hybrid VMD-BiTCN-Psformer model was devised. Firstly, VMD divided the original sequence into several data components with varying time scales. Furthermore, the BiTCN network was utilized to extract the sequence features. These features, along with the climate features, were then input into the positional encoding and ProbSparse self-attention improved Transformer model. The outputs of these models were combined to obtain the ultimate wind power prediction results. For the prediction of the wind power in Fujian Province on April 26, four additional models were developed for comparison with the VMD-BiTCN-Psformer model. The VMD-BiTCN-Psformer model demonstrated the greatest level of forecast accuracy among all the models. The R2 increased by 22.27%, 12.38%, 8.93%, and 2.59%, respectively. [ABSTRACT FROM AUTHOR]

Li metal is regarded as the "Holy Grail" in the next generation of anode materials due to its high theoretical capacity and low redox potential. However, sluggish Li ions interfacial transport kinetics and uncontrollable Li dendrites growth limit practical application of the energy storage system in high‐power device. Herein, separators are modified by the addition of a coating, which spontaneously grafts onto the Li anode interface for in situ lithiation. The resultant alloy possessing of strong electron‐donating property promotes the decomposition of lithium bistrifluoromethane sulfonimide in the electrolyte to form a LiF‐rich alloy‐doped solid electrolyte interface (SEI) layer. High ionic alloy solid solution diffusivity and electric field dispersion modulation accelerate Li ions transport and uniform stripping/plating, resulting in a high‐power dendrite‐free Li metal anode interface. Surprisingly, the formulated SEI layer achieves an ultra‐long cycle life of over 8000 h (20,000 cycles) for symmetric cells at a current density of 10 mA cm−2. It also ensures that the NCM(811)//PP@Au//Li full cell at ultra‐high currents (40 C) completes the charging/discharging process in only 68 s to provide high capacity of 151 mAh g−1. The results confirm that this scalable strategy has great development potential in realizing high power dendrite‐free Li metal anode. [ABSTRACT FROM AUTHOR]

The output power of PV systems is influenced by various factors, resulting in strong volatility and randomness, which makes it difficult to forecast. Therefore, this paper proposes an Informer prediction model based on optimised VMD for predicting short-term PV power. Firstly, the temporal coding of the Informer model is improved and, secondly, the original sequence is decomposed into multiple modal components using VMD, and then optimisation of the results of VMD in conjunction with the optimisation strategy of SSA improves the characteristics of the time series data. Finally, the refined data are fed into the Informer framework for modelling and prediction, utilising the self-attention mechanism and multiscale feature fusion of Informer to precisely forecast PV power. The power of PV prediction data from the SSA-VMD-Informer model and four other commonly used models is compared. Experimental results indicate that the SSA-VMD-Informer model performs exceptionally well in short-term PV power prediction, achieving higher accuracy than traditional methods. As an example, the results of predicting the PV power on 24 April in a region of Xinjiang are 1.3882 for RMSE, 0.8310 for MSE, 1.14 for SDE, and 0.9944 for R2. [ABSTRACT FROM AUTHOR]

Urban plant diversity is one of the key elements for sustainable urban development. Urban plant landscapes not only create a variety of experiences for residents but also have a positive effect on their physiology and psychology. In order to better introduce nature into urban green spaces, this study conducted a field survey in Nanjing, China, to analyze the current situation of spontaneous plants in Nanjing's urban green spaces and propose a plant planning strategy that takes into account both ecology and residents' well-being. This study surveyed the herbaceous plant resources in 96 sample plots in nine typical urban parks in Nanjing, and recorded 284 plant species in 192 genera and 78 families. The research results show that the differences in plant diversity, richness, and evenness among urban parks in Nanjing are significant; combined with cluster analysis and ranking results, the total area of urban parks, green space construction time, lighting conditions, and management frequency have an impact on plant communities. Further analysis of the species composition of plant communities showed that moderate management frequency in urban parks can increase plant diversity. With the advantages of both high ecological benefits and low management costs, a model of "artificial plants + native spontaneous plants" was finally proposed for the planting of herbaceous plants in sustainable urban green spaces. [ABSTRACT FROM AUTHOR]