Panpan Liu

Electrochemically active biofilms (EABs) are a class of conductive assemblies composed of electroactive microorganisms and their extracellular polymers. They have shown potential for diverse environmental applications, including bioremediation, energy conversion, and biosensing. Despite growing evidence that the hierarchical architecture and heterogeneity of EABs critically determine electron transport efficiency and biofilm function, a comprehensive review addressing these spatial features remains lacking. This paper reviews the spatial heterogeneity of EABs, discussing in detail the physicochemical microenvironment gradients, biofilm structural composition, electron transport mechanisms, and metabolic activity heterogeneity. By analyzing existing studies, the ambiguity surrounding current measurements and understanding of the heterogeneity of EABs is clarified. Finally, future research directions are proposed, including the application of advanced imaging technology and gene-editing approaches, the elucidation of the dynamic changes of biofilm heterogeneity, and the in-depth investigation of complex matrices in other ecological systems, which offer new insights into the heterogeneity and architecture of EABs. A deeper understanding of this aspect will facilitate the optimization of the microbial electrode design, configuration, and operational strategies to advance the applications of EABs.

Electrochemically active biofilm (EAB) sensors have been widely used for real-time monitoring of water biotoxicity. Although extracellular electron transfer (EET) drives the electrical signal output of EAB sensors, its relationship with sensitivity is poorly understood. This raises two critical questions: (1) Do toxicants affect EET performance? (2) What is the relationship between EET performance and sensitivity. Herein, we employed a double-electrode-controlled electrochemical gating method (EGM) to evaluate the effects of different toxicants on EET performance across multiple biological scales, ranging from mixed- and purified-species biofilms to isolated OmcA proteins. Results indicated that five representative toxicants (0.02% formaldehyde, 5 mg/L NO₂^-, 5 mg/L tobramycin, 5 mg/L Cu²⁺, and 5 mg/L SDS) rarely impacted EET performance directly. On this basis, we probed the link between EET performance and sensitivity using riboflavin (RF) and anthraquinone-2,7-disulfonate (AQDS). After a 30 min toxicity exposure, the inhibition ratios were ranked as follows: AQDS-EABs > Control > RF-EABs. Although RF observably reduced the resistance, the high capacitance weakened the sensitivity. It is suggested that reducing resistance alone could not result in a higher sensitivity, and capacitance effects cannot be overlooked through modeling and electrochemical analysis. This study, therefore, proposes the time constant as a suitable metric for evaluating the relationship between the EET performance and sensitivity.

Electrical double layer (EDL) at the interface between electrode and electrolyte dominates the electrochemical reaction progress and determines the performance of electrochemical devices. Recent findings of solvation effect, selective adsorption of ions, and product evolution at the interface pose the challenge to the understanding of classical EDL─the proposed nonclassical EDL tries to involve these aspects, and emerging measurements have been used to uncover its previously unexplored properties. These advances will reshape the strategy for designing the electrochemical devices, catalyst synthesis, and electrolyte engineering. Clarifying the features of the EDL and its characterization can be beneficial for the development of electrochemistry. In the present review, the features and characteristics of EDL will be redefined and proposed. Diverse methods used to determine and quantify the EDL are summarized to provide a clear framework for understanding the structure and behavior of the EDL. In addition, factors that affect the EDL are reviewed in diverse electrochemical reactions. This review can accelerate innovation in the field of electrochemical catalysis.

Despite nationwide control efforts, central China experiences persistently high annual PM_2.5 concentrations (~50 μg/m³), which are particularly severe in January (exceeding 110 μg/m³). This study employs an integrated approach combining a Multiple Linear Regression (MLR) model derived from random forest analysis with the WRF-CMAQ chemical transport modeling system to quantitatively disentangle the driving factors of PM_2.5 concentrations in central China. Key findings reveal significant spatiotemporal heterogeneity in anthropogenic contributions, evidenced by consistently higher north–south gradients in regression residuals (reflecting emission impacts), linked to spatially varying industrial and transportation influences. Critically, the reduction in anthropogenic impacts over six years was substantially smaller in winter (January: 27 to 23 μg/m³) compared to summer (15 to −18 μg/m³, July), highlighting the profound role of emissions in driving severe January pollution events. Furthermore, WRF-CMAQ simulations demonstrated that adverse meteorological conditions in January 2020 counteracted emission controls, causing a net increase in PM_2.5 of +13 μg/m³ relative to 2016, thereby offsetting ~68% of the reductions achieved through emission abatement (−19 μg/m³). Significant regional transport, especially affecting northern and central Henan, further weakened local control efficacy. These quantitative insights into the mechanisms of PM_2.5 pollution, particularly the counteracting effects of meteorology on emission reductions in critical winter periods, provide a vital scientific foundation for designing more effective and targeted air quality management strategies in central China.