Superior dimethyl disulfide degradation in a microbial fuel cell: Extracellular electron transfer and hybrid metabolism pathways

Biofilm metagenomic characteristics behind high coulombic efficiency for propanethiol deodorization in two-phase partitioning microbial fuel cell

Hydrophobic volatile organic sulfur compounds (VOSCs) are frequently found during sewage treatment, and their effective management is crucial for reducing malodorous complaints. Microbial fuel cells (MFC) are effective for both VOSCs abatement and energy recovery. However, the performance of MFC on VOSCs remains limited by the mass transfer efficiency of MFC in aqueous media. Inspired by two-phase partitioning biotechnology, silicone oil was introduced for the first time into MFC as a non-aqueous phase (NAP) medium to construct two-phase partitioning microbial fuel cell (TPPMFC) and augment the mass transfer of target VOSCs of propanethiol (PT) in the liquid phase. The PT removal efficiency within 32 h increased by 11-20% compared with that of single-phase MFC, and the coulombic efficiency of TPPMFC (11.01%) was 4.32-2.68 times that of single-phase MFC owing to the fact that highly active desulfurization and thiol-degrading bacteria (e.g., Pseudomonas, Achromobacter) were attached to the silicone oil surface, whereas sulfur-oxidizing bacteria (e.g., Thiobacillus, Commonas, Ottowia) were dominant on the anodic biofilm. The outer membrane cytochrome-c content and NADH dehydrogenase activity improved by 4.15 and 3.36 times in the TPPMFC, respectively. The results of metagenomics by KEGG and COG confirmed that the metabolism of PT in TPPMFC was comprehensive, and that the addition of a NAP upregulates the expression of genes related to sulfur metabolism, energy generation, and amino acid synthesis. This finding indicates that the NAP assisted bioelectrochemical systems would be promising to solve mass-transfer restrictions in low solubility contaminates removal.

Exploring ozone formation rules and concentration response to the change of precursors based on artificial neural network simulation in a typical industrial park

Industrial parks have more complex O3 formation mechanisms due to a higher concentration and more dense emission of precursors. This study establishes an artificial neural network (ANN) model with good performance by expanding the moment and concentration changes of pollutants into general variables of meteorological factors and concentrations of pollutants. Finally, the O3 formation rules and concentration response to the changes of volatile organic compounds (VOCs) and nitrogen oxides (NOx) was explored. The results showed that the studied area belonged to the NOx-sensitive regime and the sensitivity was strongly affected by relative humidity (RH) and pressure (P). The concentration of O3 tends to decrease with a higher P, lower temperature (Temp), and medium to low RH when nitric oxide (NO) is added. Conversely, at medium P, high Temp, and high RH, the addition of nitrogen dioxide (NO2) leads to a larger decrease capacity in O3 concentration. More importantly, there is a local reachable maximum incremental reactivity (MIRL) at each certain VOCs concentration level which linearly increased with VOCs. The general maximum incremental reactivity (MIR) may lead to a significant overestimation of the attainable O3 concentration in NOx-sensitive regimes. The results can significantly support the local management strategies for O3 and the precursors control.