Niche construction in a bioelectrochemical system with 3D-electrodes for efficient and thorough biodechlorination.

The design of bioelectrochemical system based on the principle of niche construction, offers a prospective pathway for achieving efficient and thorough biodechlorination in groundwater. This study designed a single-chamber microbial electrolysis cell, with porous three-dimensional (3D) electrodes introduced, to accelerate the niche construction process of functional communities. This approach allowed the growth of various bacteria capable of simultaneously degrading 2,4-dichlorophenol (DCP) and its refractory intermediates, 4-chlorophenol (4CP). The 3D-electrodes provided abundant attachment sites for diverse microbes with a high initial Shannon index (3.4), and along the degradation progress, functional bacteria (Hydrogenoanaerobacterium and Rhodococcus erythropolis for DCP-degrading, Sphingobacterium hotanense for 4CP-degrading and Delftia tsuruhatensis for phenol-degrading) constructed their niches. Applying an external voltage (0.6 V) further increased the selective pressure and niche construction pace, as well as provided 'micro-oxidation' site on the electrode surface, thereby achieving the degradation of 4CP and mineralization of phenol. The porous electrodes could also adsorb contaminants and narrow their interaction distance with microbes, which benefited the degradation efficiency. Thus a 10-fold increase in the overall mineralization of DCP was achieved. This study constructed a novel bioelectrochemical system for achieving efficient and thorough biodechlorination, which was suitable for in situ bioremediation of groundwater.

A Remote Sensing Image Super-Resolution Reconstruction Model Combining Multiple Attention Mechanisms.

Remote sensing images are characterized by high complexity, significant scale variations, and abundant details, which present challenges for existing deep learning-based super-resolution reconstruction methods. These algorithms often exhibit limited convolutional receptive fields and thus struggle to establish global contextual information, which can lead to an inadequate utilization of both global and local details and limited generalization capabilities. To address these issues, this study introduces a novel multi-branch residual hybrid attention block (MBRHAB). This innovative approach is part of a proposed super-resolution reconstruction model for remote sensing data, which incorporates various attention mechanisms to enhance performance. First, the model employs window-based multi-head self-attention to model long-range dependencies in images. A multi-branch convolution module (MBCM) is then constructed to enhance the convolutional receptive field for improved representation of global information. Convolutional attention is subsequently combined across channels and spatial dimensions to strengthen associations between different features and areas containing crucial details, thereby augmenting local semantic information. Finally, the model adopts a parallel design to enhance computational efficiency. Generalization performance was assessed using a cross-dataset approach involving two training datasets (NWPU-RESISC45 and PatternNet) and a third test dataset (UCMerced-LandUse). Experimental results confirmed that the proposed method surpassed the existing super-resolution algorithms, including Bicubic interpolation, SRCNN, ESRGAN, Real-ESRGAN, IRN, and DSSR in the metrics of PSNR and SSIM across various magnifications scales.

Enhanced trichloroethylene biodegradation: Roles of biochar-microbial collaboration beyond adsorption.

Trichloroethylene (TCE) is a pollutant widely found in groundwater, especially in the heavily contaminated industrial sites. Biological dechlorination method is environmentally friendly and low-cost. However, microorganisms grow slowly and their activity is susceptible to environmental fluctuations. This study used biochar as an additive to promote anaerobic biodegradation of TCE with mixed culture. Results showed that biochar with dose of 0.1-0.4% (w/v) brought a rapid initial decrease of TCE concentration by 39.4-88.8% in 24 h via adsorption mechanism. Biochar produced at 500 °C pyrolysis temperature (BC500) achieved the highest TCE adsorption in comparison to BC300 and BC700. Subsequently, a significantly shortened microbial stagnation phase (from 85 h to 37 h) was observed in the system with the presence of biochar. During the exponential growth phase, BC700 outperformed BC300 and BC500 in terms of TCE degradation efficiency. Electrochemical analysis demonstrated that BC700 possessed the greatest electron transfer capability. Finally, biochar shortened the time for achieving 100% removal of TCE by 54.5-69.7% (from approximate 330 h to 100-150 h). Even at high concentration of TCE (20-30 mg·L-1) that could lead to serious microbial growth inhibition, the TCE degradation efficiency could be recovered in the presence of BC500. The high-throughput sequencing data revealed that biochar promoted the relative abundance of co-metabolizing dechlorinating microorganisms (Pseudomonas, Burkholderia) in the aqueous solution, and simultaneously led to the selective colonization of reductive dechlorinating microorganisms (Enterobacteriaceae, Clostridium) attached on biochar surface. On the other hand, biochar addition decreased the relative abundance of hydrogen-competing microorganisms, thereby forming an efficient co-metabolism-reductive dechlorination system. These findings allow a better understanding of the promotion mechanism of biochar for microbial dechlorination technology supporting the biochar-assisted bioremediation in practice.