Herein, biochars derived from corn stalks, rice husks, and bamboo powder were modified by nitric acid oxidation and sodium hydroxide alkali activation to identify efficient and cost-effective polycyclic aromatic hydrocarbon-adsorbent and microbial-immobilized carriers. The surface characterization and adsorption investigation results suggested that acid/alkali modification promoted the phenanthrene removal ability in an aqueous solution of biochars via facilitating π–π/n–π electron donor–acceptor interactions, electrostatic interactions, hydrogen bonds, and hydrophobic interactions. Subsequently, the degrading bacteria Rhodococcus sp. DG1 was successfully immobilized on the rice husk-derived biochar with nitric acid oxidation (RBO), which exhibited the maximum phenanthrene adsorption efficiency (3818.99 µg·g⁻¹), abundant surface functional groups, and a larger specific surface area (182.6 m²·g⁻¹) and pore volume (0.141 m³·g⁻¹). Degradation studies revealed that the microorganisms immobilized on RBO by the adsorption method yielded a significant phenanthrene removal rate of 80.15% after 30 days, which was 38.78% higher than that of the control. Conversely, the polymer gel network-based microenvironment in the microorganism-immobilized RBO by the combined adsorption–embedding method restricted the migration and diffusion of nutrients and pollutants in the reaction system. This study thus introduces an innovative modified biochar-based microbial immobilization technology characterized by a simple design, convenient operation, and high adsorption efficiency, offering valuable insights into material selection for PAH contamination bioremediation.

In response to the significant environmental challenge posed by polycyclic aromatic hydrocarbon (PAH) contamination, extensive research efforts have focused on biochar-mediated remediation. Based on literature retrieval from the Web of Science Core Collection (WOSCC) and the Scopus database spanning the years 2000 to 2025, this paper conducts bibliometric statistical analysis of the field. Current publishing trends, leading contributing countries, influential authors and institutions, journal distributions, research hotspots and emerging directions were systematically reviewed. Furthermore, the development of biochar-mediated PAHs remediation research reveals three evolutionary stages. The initial stage centered on the foundational use of biochar for PAH pollution control, emphasizing soil contamination and optimizing the adsorption capacities of various biochars. The second stage shifted towards biochar modification techniques and applications across multiple contaminated media, while concurrently initiating the exploration of degradation and remediation methods. The research focus in the third phase has shifted towards the development of integrated synergistic remediation systems. These systems combine biochar with advanced oxidation processes and biological agents. This synergistic strategy not only enhances degradation efficiency but also overcomes the limitations of single remediation methods, such as incomplete mineralization or secondary pollution issues. The research scope has expanded from terrestrial soils to the emerging issue of PAHs in marine environments. Recent studies have begun exploring the application of algae-based and marine-specific biochar. Future research should prioritize elucidating synergistic remediation mechanisms at the molecular level, addressing the critical lack of large-scale field validation data especially for marine environments, and tailoring specific biochars to enhance remediation efficiency for PAHs in diverse media such as seawater.

Source inversion optimization using sensor observations is a key method for rapidly and accurately identifying unknown source parameters (source strength and location) in abrupt hazardous gas leaks. Sensor number and location distribution both play important roles in source inversion; however, their combined impacts on source inversion optimization remain poorly understood. In our study, the optimization inversion method is established based on the Gaussian plume model and the generation algorithm. A research strategy combining random sampling and coefficient of variation methods was proposed to simultaneously quantify their combined impacts in the case of a single emission source. The sensor layout impact difference was analyzed under varying atmospheric conditions (unstable, neutral, and stable) and source location information (known or unknown) using the Prairie Grass experiments. The results indicated that adding sensors improved the source strength estimation accuracy more when the source location was known than when it was unknown. The impacts of sensor location distribution were strongly negatively correlated (r ≤ −0.985) with the number of sensors across scenarios. For source strength estimation, the impacts of the sensor location distribution difference decreased non-linearly with more sensors for known locations but linearly for unknown ones. The impacts of sensor number and location distribution on source strength estimation were amplified under stable atmospheric conditions compared to unstable and neutral conditions. The minimum number of randomly scattered sensors required for stable source strength inversion accuracy was 11, 12, and 17 for known locations under unstable, neutral, and stable atmospheric conditions, respectively, and 24, 9, and 21 for unknown locations. The multi-layer arc distribution outperformed rectangular, single-layer arc, and downwind-axis distributions in source strength estimation. This study enhances the understanding of factors influencing source inversion optimization and provides valuable insights for optimizing sensor layouts.

Per- and polyfluoroalkyl substances (PFASs) are a global concern because of their toxicity and persistence, yet seasonal dynamics, pollution-level dependencies, and inhalation risks of PM_2.5-bound PFASs in haze-prone industrial cities remain underexplored. This study investigated 163 PM_2.5 samples collected from December 2023 to November 2024 in Jinan—a typical industrial city—and quantified 17 PFASs via LC-MS/MS. The results showed that total concentrations (∑PFASs) rank winter (133.8) > autumn (123.6) ≈ summer (123.5) > spring (97.1 pg·m⁻³). In summer and autumn, PFAS concentrations were numerically higher on clean days than on slightly polluted days. This may suggest that good air quality does not necessarily guarantee low PFAS levels. Spearman correlation analysis showed no significant monotonic relationships between ΣPFASs and individual meteorological variables. However, compound-specific responses to temperature, humidity, and wind speed exhibited chain-length dependence. Inhalation-risk evaluation of the 15 assessable PFASs showed that PFOA and short-chain PFCAs co-dominated estimated daily intake (73.1%), whereas PFOA dominated estimated risk (95.6%). Several compounds (e.g., PFHxA, PFOS) showed numerically higher risk values on clean or slightly polluted days than on polluted days. This suggests the need for species-specific evaluation. This study provides critical evidence of PFASs’ atmospheric behavior in haze-affected industrial settings and provides a scientific basis for prioritizing control species.